Triple
T22843989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flamagra |
E566162
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Takashi |
—
|
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: Takashi | Statement: [Flamagra, hasPart, Takashi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takashi Context triple: [Flamagra, hasPart, Takashi]
-
A.
Takashi
chosen
Takashi is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as arts, sports, and entertainment.
-
B.
Toshiaki
Toshiaki is a Japanese masculine given name commonly used for men and boys in Japan.
-
C.
Taisuke
Taisuke is a Japanese given name notably borne by historical figures such as the Meiji-era politician Itagaki Taisuke.
-
D.
Toshiki
Toshiki is a Japanese masculine given name borne by various notable individuals in politics, entertainment, and sports.
-
E.
Takatoshi
Takatoshi is a masculine Japanese given name that can be written with various kanji combinations and is borne by multiple notable individuals in Japan.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e8726d4819095b4d999b4172ff7 |
completed | April 29, 2026, 3:44 a.m. |
Created at: April 17, 2026, 3:36 p.m.