Triple
T19339204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Béziers Cap d’Agde Airport |
E483704
|
entity |
| Predicate | hasCode |
P9567
|
FINISHED |
| Object | LFMU |
—
|
NE NERFINISHED |
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: LFMU | Statement: [Béziers Cap d’Agde Airport, hasCode, LFMU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LFMU Context triple: [Béziers Cap d’Agde Airport, hasCode, LFMU]
-
A.
LFMU
chosen
LFMU is the ICAO airport code for Béziers Cap d’Agde Airport, a regional airport in southern France serving the Béziers and Cap d’Agde area.
-
B.
LFMN
LFMN is the ICAO airport code for Nice Côte d’Azur Airport, a major international airport serving Nice and the French Riviera in southeastern France.
-
C.
LFMK
LFMK is the ICAO airport code for Carcassonne Airport in southern France, which serves the city of Carcassonne and the surrounding Occitanie region.
-
D.
LFML
LFML is the ICAO airport code for Marseille Provence Airport, a major international airport serving the city of Marseille and the Provence region in southern France.
-
E.
LF
LF is a German vehicle registration code assigned to the Traunstein district in the state of Bavaria.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e618560f0081908565f802ea1e3cc8 |
completed | April 20, 2026, 12:13 p.m. |
Created at: April 10, 2026, 1:33 p.m.