Triple
T14105930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TFX |
E339503
|
entity |
| Predicate | ownedBy |
P347
|
FINISHED |
| Object | Bouygues (via TF1 Group) |
E132001
|
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: Bouygues (via TF1 Group) | Statement: [TFX, ownedBy, Bouygues (via TF1 Group)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bouygues (via TF1 Group) Context triple: [TFX, ownedBy, Bouygues (via TF1 Group)]
-
A.
Bouygues
chosen
Bouygues is a major French industrial group primarily active in construction, real estate development, media, and telecommunications.
-
B.
TF1 Group
TF1 Group is a major French media conglomerate best known for operating France’s leading television channel TF1 and various other broadcasting and digital media assets.
-
C.
France Télécom
France Télécom was the former state-owned French telecommunications company that evolved into Orange S.A., a major global telecom operator.
-
D.
Groupe TVA
Groupe TVA is a major Canadian French-language media company that operates television networks, specialty channels, and related media services, primarily in Quebec.
-
E.
Lagardère Group
Lagardère Group is a major French multinational media conglomerate with core businesses in publishing, travel retail, and entertainment.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de600ada808190b92d67dc30f13d15 |
completed | April 14, 2026, 3:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0b48e448190b4fb8cb33e5d97e6 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:22 p.m.