Triple
T10014914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aichi Prefecture |
E199464
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Anjō
Anjō is a city in central Japan known for its manufacturing industries and location within the Chūbu region on Honshu.
|
E976766
|
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: Anjō | Statement: [Aichi Prefecture, containsCity, Anjō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anjō Context triple: [Aichi Prefecture, containsCity, Anjō]
-
A.
Yame
Yame is a city in southwestern Japan renowned for its high-quality green tea production and traditional crafts.
-
B.
Maibara
Maibara is a city in Shiga Prefecture, Japan, known as a regional transportation hub with a Shinkansen station and scenic views of nearby Lake Biwa and surrounding mountains.
-
C.
Ōsaki
Ōsaki is a major commercial and business district in Tokyo known for its high-rise office complexes and convenient rail connections.
-
D.
Izumisano
Izumisano is a coastal city in Osaka Prefecture, Japan, known as the mainland gateway to Kansai International Airport and a hub for regional commerce and travel.
-
E.
Ashiya
Ashiya is an affluent coastal city in Japan’s Hyōgo Prefecture, known for its upscale residential neighborhoods and proximity to both Kobe and Osaka.
- 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: Anjō Triple: [Aichi Prefecture, containsCity, Anjō]
Generated description
Anjō is a city in central Japan known for its manufacturing industries and location within the Chūbu region on Honshu.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anjō Target entity description: Anjō is a city in central Japan known for its manufacturing industries and location within the Chūbu region on Honshu.
-
A.
Yame
Yame is a city in southwestern Japan renowned for its high-quality green tea production and traditional crafts.
-
B.
Maibara
Maibara is a city in Shiga Prefecture, Japan, known as a regional transportation hub with a Shinkansen station and scenic views of nearby Lake Biwa and surrounding mountains.
-
C.
Ōsaki
Ōsaki is a major commercial and business district in Tokyo known for its high-rise office complexes and convenient rail connections.
-
D.
Izumisano
Izumisano is a coastal city in Osaka Prefecture, Japan, known as the mainland gateway to Kansai International Airport and a hub for regional commerce and travel.
-
E.
Ashiya
Ashiya is an affluent coastal city in Japan’s Hyōgo Prefecture, known for its upscale residential neighborhoods and proximity to both Kobe and Osaka.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd49b19c8190b429e3533d072648 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a6efa448190a9d95c5bd68ff34b |
completed | May 2, 2026, 4:46 p.m. |
| NEDg | Description generation | batch_69f62be354a88190aaf5e8439b33120b |
completed | May 2, 2026, 4:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62c8194d881909db3d320a21f2052 |
completed | May 2, 2026, 4:55 p.m. |
Created at: March 30, 2026, 8:52 p.m.