Triple
T2786809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawasaki |
E61828
|
entity |
| Predicate | hasWard |
P14475
|
FINISHED |
| Object |
Tama-ku
Tama-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known for its residential areas and proximity to Tokyo.
|
E442693
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tama-ku | Statement: [Kawasaki, hasWard, Tama-ku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tama-ku Context triple: [Kawasaki, hasWard, Tama-ku]
-
A.
Toshima
Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
-
B.
Naniwa-ku
Naniwa-ku is a central ward of Osaka, Japan, known for its bustling entertainment districts, shopping streets, and iconic landmarks such as Tsutenkaku Tower.
-
C.
Taihaku-ku
Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
-
D.
Nakahara-ku
Nakahara-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known as a residential and commercial area within the Greater Tokyo metropolitan region.
-
E.
Minami-ku
Minami-ku is one of the wards of Fukuoka City in Japan, known as a primarily residential area with local commercial centers and public facilities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tama-ku Triple: [Kawasaki, hasWard, Tama-ku]
Generated description
Tama-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known for its residential areas and proximity to Tokyo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tama-ku Target entity description: Tama-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known for its residential areas and proximity to Tokyo.
-
A.
Toshima
Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
-
B.
Naniwa-ku
Naniwa-ku is a central ward of Osaka, Japan, known for its bustling entertainment districts, shopping streets, and iconic landmarks such as Tsutenkaku Tower.
-
C.
Taihaku-ku
Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
-
D.
Nakahara-ku
Nakahara-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known as a residential and commercial area within the Greater Tokyo metropolitan region.
-
E.
Minami-ku
Minami-ku is one of the wards of Fukuoka City in Japan, known as a primarily residential area with local commercial centers and public facilities.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddb0d3488190a3f2bf47ebb35802 |
completed | March 7, 2026, 8:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b62788456c8190a484826e5d915d9a |
completed | March 15, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69b628fe10908190978dd0361628f54f |
completed | March 15, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b629ab52c881909f7fbef6f77b5bc4 |
completed | March 15, 2026, 3:38 a.m. |
Created at: March 6, 2026, 9:57 p.m.