Triple
T10410592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salon du Bourget |
E245377
|
entity |
| Predicate | organizer |
P123
|
FINISHED |
| Object | GIFAS |
E245376
|
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: GIFAS | Statement: [Salon du Bourget, organizer, GIFAS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GIFAS Context triple: [Salon du Bourget, organizer, GIFAS]
-
A.
GIFAS
chosen
GIFAS (Groupement des Industries Françaises Aéronautiques et Spatiales) is the French aerospace industries association representing and promoting France’s aviation, space, and defense sectors.
-
B.
GAFI
GAFI is the French acronym for the Financial Action Task Force, an intergovernmental body that sets global standards to combat money laundering, terrorist financing, and related financial crimes.
-
C.
GIFF
GIFF is the commonly used acronym for the Gothenburg Film Festival, one of the leading and largest film festivals in Scandinavia.
-
D.
GFA
GFA is the ICAO airline designator used for Gulf Air, the national carrier of Bahrain.
-
E.
GUF
GUF is the three-letter ISO 3166-1 alpha-3 country code assigned to French Guiana.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9fb98748190a3a6c161edd8f400 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e9084fc81909e1d46a111a1ef2b |
completed | April 10, 2026, 4:37 a.m. |
Created at: April 6, 2026, 12:09 p.m.