Triple
T6456340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MIPTV |
E142001
|
entity |
| Predicate | organizer |
P123
|
FINISHED |
| Object | RX France |
E582390
|
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: RX France | Statement: [MIPTV, organizer, RX France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RX France Context triple: [MIPTV, organizer, RX France]
-
A.
RX France
chosen
RX France is a major global events and exhibitions organizer known for producing leading trade shows and industry gatherings across diverse sectors.
-
B.
Radio France
Radio France is France’s national public radio broadcaster, operating multiple nationwide stations that provide news, culture, music, and educational programming.
-
C.
France 3
France 3 is a French public television channel known for its regional programming and news coverage as part of the France Télévisions group.
-
D.
France 2
France 2 is a major French public television channel that forms part of the France Télévisions group and broadcasts a wide range of news, entertainment, and cultural programming nationwide.
-
E.
CA Roissy Pays de France
CA Roissy Pays de France is a French intercommunal structure in the Île-de-France region that groups together several municipalities around Roissy, including those near Paris-Charles de Gaulle Airport, to coordinate local development and public services.
- 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_69c008d2f91c8190a8178767a35e08fc |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069d639ec8190bb0a806da4118440 |
completed | March 22, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bdc4e808190a7c24b963ab0aa30 |
completed | March 27, 2026, 9:20 a.m. |
Created at: March 22, 2026, 4:48 p.m.