Triple
T16814333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daikanyama Station |
E408700
|
entity |
| Predicate | locatedInWard |
P40
|
FINISHED |
| Object | Shibuya-ku |
—
|
NE NERFINISHED |
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: Shibuya-ku | Statement: [Daikanyama Station, locatedInWard, Shibuya-ku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shibuya-ku Context triple: [Daikanyama Station, locatedInWard, Shibuya-ku]
-
A.
Shibuya-ku
chosen
Shibuya-ku is a major commercial and entertainment ward in central Tokyo, Japan, known for its bustling shopping districts, nightlife, and the iconic Shibuya Crossing.
-
B.
Shinjuku-ku
Shinjuku-ku is a major commercial and administrative ward in central Tokyo, Japan, known for its bustling shopping districts, skyscrapers, and one of the world’s busiest railway stations.
-
C.
Chūō-ku
Chūō-ku is a central ward of Osaka, Japan, known as a major commercial and entertainment hub featuring famous landmarks, shopping streets, and nightlife areas.
-
D.
Chūō-ku
Chūō-ku is a central ward of Tokyo, Japan, known as a major commercial and business district that includes areas like Ginza and Nihonbashi.
-
E.
Chūō-ku
Chūō-ku is a central ward of Fukuoka City in Japan, known as a major commercial, entertainment, and administrative hub.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b2e01fb8819081cf2c08f29448da |
completed | April 18, 2026, 4:35 p.m. |
Created at: April 10, 2026, 5:23 a.m.