Triple
T20282136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayashi |
E503174
|
entity |
| Predicate | romanizedAs |
P2508
|
FINISHED |
| Object | Hayashi |
—
|
NE NERFINISHED |
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: Hayashi | Statement: [Hayashi, romanizedAs, Hayashi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hayashi Context triple: [Hayashi, romanizedAs, Hayashi]
-
A.
Hayashi
chosen
Hayashi is a common Japanese surname that literally means "forest" and is equivalent to the Chinese surname "Lin."
-
B.
Hisashi
Hisashi is a Japanese masculine given name borne by various notable individuals in fields such as law, politics, sports, and the arts.
-
C.
Yukuhashi
Yukuhashi is a city in eastern Fukuoka Prefecture, Japan, known as a regional commercial and transportation hub on Kyushu.
-
D.
Fukuhara
Fukuhara was a historical port district in present-day Kobe, Japan, that briefly served as the seat of the imperial court and political center during the late Heian period.
-
E.
Hayakawa
Hayakawa is a Japanese surname borne by numerous notable individuals in fields such as film, politics, and academia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6768f86448190842389a98b93a918 |
completed | April 20, 2026, 6:55 p.m. |
Created at: April 16, 2026, 10:39 a.m.