Triple
T11969731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawanishi |
E284884
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object |
Ikeda
Ikeda is a city in Osaka Prefecture, Japan, known as a residential and industrial suburb within the Kansai region.
|
E956391
|
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: Ikeda | Statement: [Kawanishi, neighboringMunicipality, Ikeda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ikeda Context triple: [Kawanishi, neighboringMunicipality, Ikeda]
-
A.
Ikeda
Ikeda is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and academia.
-
B.
Murayama
Murayama is a Japanese surname borne by various notable individuals across fields such as politics, science, and the arts.
-
C.
Ichikawa
Ichikawa is a city in Chiba Prefecture, Japan, located just east of Tokyo and known as a residential and commercial hub within the Greater Tokyo Area.
-
D.
Ichigaya
Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
-
E.
Yoshida
Yoshida is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and entertainment.
- 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: Ikeda Triple: [Kawanishi, neighboringMunicipality, Ikeda]
Generated description
Ikeda is a city in Osaka Prefecture, Japan, known as a residential and industrial suburb within the Kansai region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ikeda Target entity description: Ikeda is a city in Osaka Prefecture, Japan, known as a residential and industrial suburb within the Kansai region.
-
A.
Ikeda
Ikeda is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and academia.
-
B.
Murayama
Murayama is a Japanese surname borne by various notable individuals across fields such as politics, science, and the arts.
-
C.
Ichikawa
Ichikawa is a city in Chiba Prefecture, Japan, located just east of Tokyo and known as a residential and commercial hub within the Greater Tokyo Area.
-
D.
Ichigaya
Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
-
E.
Yoshida
Yoshida is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and entertainment.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037bee54819085242a3ef3e286f9 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f459691ff0819099282172933d2d81 |
completed | May 1, 2026, 7:42 a.m. |
| NEDg | Description generation | batch_69f4645ef63881909b46937f73d637a3 |
completed | May 1, 2026, 8:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f465be4db08190882898a17d077019 |
completed | May 1, 2026, 8:35 a.m. |
Created at: April 8, 2026, 9:46 p.m.