Triple
T18790601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LIL |
E459502
|
entity |
| Predicate | identifies |
P310
|
FINISHED |
| Object | Lille Airport |
—
|
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: Lille Airport | Statement: [LIL, identifies, Lille Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lille Airport Context triple: [LIL, identifies, Lille Airport]
-
A.
Lille Airport
chosen
Lille Airport is an international airport serving the city of Lille and the surrounding Hauts-de-France region in northern France.
-
B.
Strasbourg Airport
Strasbourg Airport is an international airport serving the city of Strasbourg and the surrounding Alsace region in northeastern France.
-
C.
Liège Airport
Liège Airport is a major international cargo and passenger airport in eastern Belgium, known as one of Europe’s leading freight hubs.
-
D.
Beauvais–Tillé Airport
Beauvais–Tillé Airport is a secondary international airport serving the Paris region, known primarily as a hub for low-cost carriers and budget flights.
-
E.
Le Touquet – Côte d’Opale Airport
Le Touquet – Côte d’Opale Airport is a regional airport in northern France serving the seaside resort town of Le Touquet-Paris-Plage and the surrounding Côte d’Opale area.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5978599008190aaceaff1b1e0a2c7 |
completed | April 20, 2026, 3:03 a.m. |
Created at: April 10, 2026, 11:53 a.m.