Triple
T18403577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montpellier-Méditerranée Airport |
E450059
|
entity |
| Predicate | ICAO code |
P419
|
FINISHED |
| Object | LFMT |
—
|
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: LFMT | Statement: [Montpellier-Méditerranée Airport, ICAO code, LFMT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LFMT Context triple: [Montpellier-Méditerranée Airport, ICAO code, LFMT]
-
A.
LFMT
chosen
LFMT is the ICAO airport code for Montpellier–Méditerranée Airport, a regional international airport serving the city of Montpellier in southern France.
-
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.
LF
LF is a German vehicle registration code assigned to the Traunstein district in the state of Bavaria.
-
D.
LF
LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
-
E.
LFMK
LFMK is the ICAO airport code for Carcassonne Airport in southern France, which serves the city of Carcassonne and the surrounding Occitanie region.
- 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e5195509cc8190bd4e91adb9b4a0ce |
completed | April 19, 2026, 6:05 p.m. |
Created at: April 10, 2026, 10:46 a.m.