Triple
T6746296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kotoshironushi |
E154224
|
entity |
| Predicate | identifiedWith |
P13264
|
FINISHED |
| Object | Ebisu |
E29485
|
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: Ebisu | Statement: [Kotoshironushi, identifiedWith, Ebisu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ebisu Context triple: [Kotoshironushi, identifiedWith, Ebisu]
-
A.
Ebisu
chosen
Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
-
B.
Shiba
Shiba is a central district in Minato, Tokyo, known for its mix of historic temples, business centers, and residential areas.
-
C.
Kurō
Kurō is an honorific name historically associated with the famed Japanese military commander Minamoto no Yoshitsune of the late Heian period.
-
D.
Hamachō
Hamachō is a neighborhood in Chūō ward, central Tokyo, known for its mix of residential areas, local businesses, and proximity to the Nihonbashi district.
-
E.
Kunoy
Kunoy is a small, mountainous island in the Faroe Islands known for its dramatic cliffs, sparse population, and traditional fishing villages.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1b8a0f0819086b802983e8ffcb6 |
completed | March 27, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b15ded88190a36fb86093ba5a3c |
completed | March 27, 2026, 10:56 p.m. |
Created at: March 27, 2026, 2:10 p.m.