Triple
T10297008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Setagaya |
E241517
|
entity |
| Predicate | hasBorderWith |
P224
|
FINISHED |
| Object | Ōta |
E300642
|
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: Ōta | Statement: [Setagaya, hasBorderWith, Ōta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ōta Context triple: [Setagaya, hasBorderWith, Ōta]
-
A.
Ōta
chosen
Ōta is a special ward in southern Tokyo, Japan, known for Haneda Airport and its mix of residential, industrial, and coastal areas.
-
B.
Otsuka
Otsuka is a neighborhood in Tokyo known for its mix of traditional shopping streets, residential areas, and convenient rail connections, including the JR Yamanote Line.
-
C.
Keiyo
Keiyo is a Southern Nilotic language spoken primarily by the Keiyo people of Kenya’s Rift Valley region.
-
D.
Mitaka
Mitaka is a city in western Tokyo, Japan, known for its residential neighborhoods, parks, and the Ghibli Museum.
-
E.
Gotō
Gotō is a Japanese surname borne by various notable figures in politics, business, and the arts.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2ebd258819099fadddcd13099fc |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d2cc9c48190bc36f6a4f8144b7f |
completed | April 9, 2026, 3:29 a.m. |
Created at: April 6, 2026, 11:43 a.m.