Triple
T9851430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuuk International Airport |
E239478
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Weno |
E46818
|
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: Weno | Statement: [Chuuk International Airport, locatedIn, Weno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weno Context triple: [Chuuk International Airport, locatedIn, Weno]
-
A.
Weno
chosen
Weno is the main urban and commercial center of Chuuk State in the Federated States of Micronesia, known for its lagoon setting and role as a regional hub.
-
B.
Weno Harbor
Weno Harbor is the main maritime harbor serving the island town of Weno in Chuuk State, Micronesia, functioning as a key hub for local transportation and trade.
-
C.
Wounaan
The Wounaan are an Indigenous people of Panama and Colombia known for their rich rainforest-based culture, intricate basketry, and traditional practices closely tied to riverine environments.
-
D.
Badaguan
Badaguan is a scenic coastal area in Qingdao famous for its tree-lined streets, historic European-style villas, and popular seaside promenades.
-
E.
Wando
Wando is a coastal city and island hub in South Jeolla Province, South Korea, known for its fisheries, seaweed production, and scenic maritime landscapes.
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3742fe48190bae6e6d828a9cc0d |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5ee190c8190957451d8d8291df3 |
completed | April 5, 2026, 3:24 a.m. |
Created at: March 30, 2026, 8:34 p.m.