Triple
T12592615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ōta |
E300642
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Haneda area |
E622623
|
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: Haneda area | Statement: [Ōta, hasPart, Haneda area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haneda area Context triple: [Ōta, hasPart, Haneda area]
-
A.
Haneda area
chosen
Haneda area is a district in Tokyo’s Ōta Ward best known for encompassing Haneda Airport, one of Japan’s major international air hubs.
-
B.
Azabu area
The Azabu area is a central Tokyo neighborhood known for its upscale residential streets, international community, embassies, and proximity to Roppongi and other major districts.
-
C.
Aoyama area
The Aoyama area is an upscale Tokyo neighborhood known for its fashionable boutiques, contemporary architecture, and trendy cafes and galleries.
-
D.
Yokokawa area
The Yokokawa area is one of the three main temple precincts of Enryaku-ji on Mount Hiei, known for its secluded, forested setting and historic Buddhist halls.
-
E.
Suidobashi area
Suidobashi area is a central Tokyo neighborhood known for its major train station, proximity to Tokyo Dome City and universities, and mix of entertainment, sports, and office facilities.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cc6d3c81908fbb22601c46f3f7 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ec2dac88190bf31bb00f93feb30 |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 9, 2026, 5:07 p.m.