Triple
T1365569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kobe Port Tower |
E29194
|
entity |
| Predicate | locatedInArea |
P40
|
FINISHED |
| Object | Kobe waterfront |
E135864
|
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: Kobe waterfront | Statement: [Kobe Port Tower, locatedInArea, Kobe waterfront]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobe waterfront Context triple: [Kobe Port Tower, locatedInArea, Kobe waterfront]
-
A.
Kobe
Kobe is a major port city in Japan’s Kansai region, known for its scenic harbor setting, cosmopolitan atmosphere, and famous Kobe beef.
-
B.
Kobe Chinatown
Kobe Chinatown is a compact, bustling Chinese district in central Kobe, Japan, known for its vibrant streets, food stalls, and cultural festivals.
-
C.
Kobe Harborland Center Building
Kobe Harborland Center Building is a commercial high-rise complex in Kobe, Japan, featuring offices, shops, and entertainment facilities within the Kobe Harborland waterfront district.
-
D.
Harborland, Kobe
chosen
Harborland, Kobe is a popular waterfront shopping and entertainment district in Kobe, Japan, known for its malls, restaurants, and scenic harbor views.
-
E.
Odaiba
Odaiba is a popular high-tech entertainment and shopping district built on a man-made island in Tokyo Bay.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2d1d15481909d58b6fd8aa2e585 |
completed | March 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1596d1c8819081e65469302873ba |
completed | March 8, 2026, 6:22 a.m. |
Created at: March 1, 2026, 7:57 p.m.