Triple
T7248578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kobe Airport |
E156537
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kobe |
E3089
|
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 | Statement: [Kobe Airport, locatedIn, Kobe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobe Context triple: [Kobe Airport, locatedIn, Kobe]
-
A.
Kobe
chosen
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 Nankinmachi
Kobe Nankinmachi is a famous Chinatown district in Kobe, Japan, known for its Chinese restaurants, shops, and vibrant cultural festivals.
-
C.
Kobe, Hyogo, Japan
Kobe, Hyogo, Japan is a major port city in western Japan known for its international trade, scenic harbor setting between mountains and sea, and famous Kobe beef.
-
D.
Kobe waterfront redevelopment area
The Kobe waterfront redevelopment area is a revitalized coastal district in Kobe, Japan, featuring parks, cultural attractions, and commercial facilities that showcase the city’s modern harborfront.
-
E.
Nada-ku, Kobe
Nada-ku, Kobe is a ward of Kobe, Japan, known for its scenic Mount Rokko area, sake breweries, and residential neighborhoods.
- 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_69c68827b5e481908dc05e145b2c92d4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea763f208190af1210cd8d2a05c9 |
completed | March 27, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db1278b08190bab9f01287040492 |
completed | March 28, 2026, 1:43 p.m. |
Created at: March 27, 2026, 2:56 p.m.