Triple
T8887835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansai Kūkō |
E211578
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Sennan |
E222425
|
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: Sennan | Statement: [Kansai Kūkō, locatedNear, Sennan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sennan Context triple: [Kansai Kūkō, locatedNear, Sennan]
-
A.
Sennan
chosen
Sennan is a coastal city in Osaka Prefecture, Japan, known for its proximity to Kansai International Airport and its role as part of the greater Osaka metropolitan area.
-
B.
Miyazya
Miyazya is one of the spring months in the Ethiopian calendar, roughly corresponding to April in the Gregorian calendar.
-
C.
Sannomiya
Sannomiya is a major commercial and transportation hub in central Kobe, Japan, known for its shopping streets, nightlife, and role as the city’s downtown core.
-
D.
Shimaore
Shimaore is a Bantu language closely related to Comorian, widely spoken by the local population of Mayotte in the Indian Ocean.
-
E.
Sakae
Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
- 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_69ca83907954819096d52a245b635841 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc618e58d08190be3ebcbe3701b1db |
completed | April 1, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfabe17c78819087e74618ac49a214 |
completed | April 3, 2026, noon |
Created at: March 30, 2026, 6:53 p.m.