Triple
T5522489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel Crozier |
E144843
|
entity |
| Predicate | coAuthor |
P398
|
FINISHED |
| Object | Joji Watanuki |
E302870
|
NE FINISHED |
How this triple was built (2 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: Joji Watanuki | Statement: [Michel Crozier, coAuthor, Joji Watanuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joji Watanuki Context triple: [Michel Crozier, coAuthor, Joji Watanuki]
-
A.
Joji Watanuki
chosen
Joji Watanuki is a political scientist known for his collaborative work with Samuel P. Huntington on comparative politics and political development.
-
B.
Kei Satō
Kei Satō is a Japanese politician and member of the House of Councillors known for his involvement in contemporary national politics.
-
C.
Ryo Satō
Ryo Satō is a Japanese personal name shared by multiple individuals, commonly appearing in contexts such as sports, entertainment, and other public professions in Japan.
-
D.
Rippei Ogisu
Rippei Ogisu was an Imperial Japanese Army officer best known for his command role in the 1939 Battle of Khalkhin Gol against Soviet–Mongolian forces.
-
E.
Sanjo Ohashi
Sanjo Ohashi is a historic bridge in Kyoto, Japan, long regarded as a key terminus of the Tōkaidō road and an important crossing point in the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008f873a481909b4d9f7e2db3c37d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f73cc8c8190a92a839c1ca804c7 |
completed | March 22, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d189c795d48190ba80739d07bc899c |
completed | April 4, 2026, 9:59 p.m. |
Created at: March 22, 2026, 3:34 p.m.