Triple
T17102380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tama area |
E415010
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Kodaira |
E346139
|
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: Kodaira | Statement: [Tama area, hasPart, Kodaira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kodaira Context triple: [Tama area, hasPart, Kodaira]
-
A.
Kodaira
chosen
Kodaira is a suburban city in western Tokyo, Japan, known as a residential area with parks, schools, and convenient rail access to central Tokyo.
-
B.
Koyama
Koyama is a Japanese surname borne by various notable individuals across fields such as entertainment, sports, and the arts.
-
C.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
D.
Wakamatsu
Wakamatsu is a ward in the city of Kitakyushu, Japan, known historically as a port and industrial area on the northern coast of Kyushu.
-
E.
Kawaguchi
Kawaguchi is a major commuter city in the Greater Tokyo area of Japan, located just north of Tokyo in Saitama Prefecture.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc239a088190a776fe0f4361ffc7 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b2d499de08190b0de4b4211936aec |
completed | May 18, 2026, 3:16 p.m. |
Created at: April 10, 2026, 5:35 a.m.