Triple
T6619044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John A. Osborne Airport |
E149627
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object | Brades |
E98377
|
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: Brades | Statement: [John A. Osborne Airport, servesCity, Brades]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brades Context triple: [John A. Osborne Airport, servesCity, Brades]
-
A.
Brades
chosen
Brades is a town on the Caribbean island of Montserrat that serves as the territory’s temporary administrative and commercial center following the abandonment of Plymouth due to volcanic activity.
-
B.
Bankal
Bankal is a Jarawan Bantu language spoken by a small ethnic community in Nigeria.
-
C.
BRI
BRI is one of Indonesia’s largest and oldest state-owned banks, known for its extensive microfinance and rural banking services.
-
D.
BRI
BRI is a global infrastructure and economic development strategy launched by China to enhance trade and connectivity across Asia, Europe, Africa, and beyond.
-
E.
Barclay
Barclay is a brand of cigarettes introduced by Brown & Williamson, known for its low-tar marketing and distinctive filter design.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af5ca97481909f8a7dc47249b4d3 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e4461e748190b4feead6ef16a01c |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:58 p.m.