Triple
T2327791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saitama Prefecture |
E48329
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Koshigaya
Koshigaya is a suburban city in Japan known for its large shopping complexes and residential communities within the Greater Tokyo metropolitan area.
|
E452935
|
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: Koshigaya | Statement: [Saitama Prefecture, hasCity, Koshigaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koshigaya Context triple: [Saitama Prefecture, hasCity, Koshigaya]
-
A.
Higashimurayama
Higashimurayama is a suburban city in western Tokyo, Japan, known for its residential neighborhoods, parks, and role as part of the Tama area’s commuter belt.
-
B.
Osakasayama
Osakasayama is a suburban city in Osaka Prefecture, Japan, known for its residential character and proximity to the Osaka metropolitan area.
-
C.
Kakogawa
Kakogawa is an industrial and residential city in central Hyōgo Prefecture, Japan, known for its steel manufacturing and role as a regional transportation hub.
-
D.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
E.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
- 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: Koshigaya Triple: [Saitama Prefecture, hasCity, Koshigaya]
Generated description
Koshigaya is a suburban city in Japan known for its large shopping complexes and residential communities within the Greater Tokyo metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Koshigaya Target entity description: Koshigaya is a suburban city in Japan known for its large shopping complexes and residential communities within the Greater Tokyo metropolitan area.
-
A.
Higashimurayama
Higashimurayama is a suburban city in western Tokyo, Japan, known for its residential neighborhoods, parks, and role as part of the Tama area’s commuter belt.
-
B.
Osakasayama
Osakasayama is a suburban city in Osaka Prefecture, Japan, known for its residential character and proximity to the Osaka metropolitan area.
-
C.
Kakogawa
Kakogawa is an industrial and residential city in central Hyōgo Prefecture, Japan, known for its steel manufacturing and role as a regional transportation hub.
-
D.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
E.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc64c7f1881909b0d847f7782e803 |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdc4fea8fc8190bf99d53fc56d7d39 |
completed | March 20, 2026, 10:06 p.m. |
| NEDg | Description generation | batch_69bdc95cabc081909c2174d5a1145edc |
completed | March 20, 2026, 10:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdca0d95308190b3b52d6f046fbf0e |
completed | March 20, 2026, 10:28 p.m. |
Created at: March 4, 2026, 7:50 p.m.