Triple
T7528485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faaʻa International Airport |
E177954
|
entity |
| Predicate | servesAirline |
P12356
|
FINISHED |
| Object | French Bee |
E10909
|
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: French Bee | Statement: [Faaʻa International Airport, servesAirline, French Bee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: French Bee Context triple: [Faaʻa International Airport, servesAirline, French Bee]
-
A.
French Bee
chosen
French Bee is a French low-cost, long-haul airline specializing in transatlantic and Indian Ocean routes.
-
B.
Bee
Bee is a common English surname shared by various individuals, including the comedian and television host Samantha Bee.
-
C.
Beeby
Beeby is a surname most notably associated with American architect Thomas Beeby, a prominent figure in postmodern and classical revival design.
-
D.
Barberini bees
The Barberini bees are a heraldic emblem of the powerful Italian Barberini family, prominently associated with Pope Urban VIII and widely used in Baroque art and architecture in Rome.
-
E.
The Bee
The Bee is the 16th chapter of the Qur'an, known for its emphasis on God's blessings, signs in nature, and guidance for righteous living.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81e19208190965f211d057f7fdf |
completed | March 27, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84639c19881909e1736afc01a020d |
completed | March 28, 2026, 9:20 p.m. |
Created at: March 27, 2026, 3:47 p.m.