Triple
T1124189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiyukan |
E24681
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Minato-ku, Osaka |
E284120
|
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: Minato-ku, Osaka | Statement: [Kaiyukan, locatedIn, Minato-ku, Osaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minato-ku, Osaka Context triple: [Kaiyukan, locatedIn, Minato-ku, Osaka]
-
A.
Minato-ku, Osaka
chosen
Minato-ku, Osaka is a coastal ward of Osaka City known for its waterfront attractions, including major entertainment, shopping, and port facilities.
-
B.
Yodogawa-ku, Osaka
Yodogawa-ku, Osaka is a ward in northern Osaka City known as a major transportation hub, notably hosting Shin-Osaka Station, the city’s primary Shinkansen terminal.
-
C.
Konohana-ku, Osaka
Konohana-ku, Osaka is a ward of Osaka City in Japan known for hosting major attractions like Universal Studios Japan and its themed entertainment areas.
-
D.
Chuo-ku, Osaka
Chuo-ku, Osaka is a central ward of Osaka City known as a major commercial, business, and entertainment hub.
-
E.
Tennoji-ku, Osaka
Tennoji-ku, Osaka is a central ward of Osaka City known for its major transport hub, historic Shitenno-ji Temple, and large commercial and shopping complexes.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bbd92a8c8190a16e55f3f739010f |
completed | March 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc00ddbf48190866fb79b4b4a2857 |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 1, 2026, 7:44 p.m.