Triple
T14066862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiroshi Hara |
E338497
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hiroshi |
E483914
|
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: Hiroshi | Statement: [Hiroshi Hara, givenName, Hiroshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hiroshi Context triple: [Hiroshi Hara, givenName, Hiroshi]
-
A.
Hiroshi
chosen
Hiroshi is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as art, politics, and entertainment.
-
B.
Yasuhiro
Yasuhiro is a Japanese masculine given name borne by various notable figures in politics, sports, and entertainment.
-
C.
Shigeo
Shigeo is a Japanese given name commonly used for males.
-
D.
Hirofumi
Hirofumi is a Japanese given name commonly borne by men, including notable contemporary politicians.
-
E.
Takehiro
Takehiro is a central character in Ryūnosuke Akutagawa’s short story “In a Grove,” whose ambiguous fate is revealed through conflicting eyewitness testimonies.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568b81f08190a571004261c0e8e4 |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb710b34819094e3387a3ef6fcff |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 9, 2026, 10:21 p.m.