Triple
T9942925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ichirō Hatoyama |
E194127
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ichirō |
E727278
|
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: Ichirō | Statement: [Ichirō Hatoyama, givenName, Ichirō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ichirō Context triple: [Ichirō Hatoyama, givenName, Ichirō]
-
A.
Ichirō
chosen
Ichirō is a common Japanese masculine given name that can be written with various kanji and is often associated with first-born sons.
-
B.
Kinnosuke
Kinnosuke is the given name of the renowned Japanese novelist Natsume Sōseki, a central figure in modern Japanese literature.
-
C.
Kenjirō
Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
-
D.
Shinpei
Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, and entertainment.
-
E.
Tadahiko
Tadahiko is a Japanese masculine given name used by various notable individuals in fields such as sports, arts, and academia.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb6124a188190b41feadb7b2f8922 |
completed | April 2, 2026, 12:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbd9073c948190aa2e9e6b7ffe9022 |
completed | April 12, 2026, 5:40 p.m. |
Created at: March 30, 2026, 8:45 p.m.