Triple
T9510278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claude Berrou |
E229372
|
entity |
| Predicate | affiliation |
P10
|
FINISHED |
| Object | Télécom Bretagne |
E791727
|
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: Télécom Bretagne | Statement: [Claude Berrou, affiliation, Télécom Bretagne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Télécom Bretagne Context triple: [Claude Berrou, affiliation, Télécom Bretagne]
-
A.
Télécom Bretagne
chosen
Télécom Bretagne was a leading French grande école and engineering school specializing in telecommunications and information technologies, later integrated into IMT Atlantique.
-
B.
France Télécom
France Télécom was the former state-owned French telecommunications company that evolved into Orange S.A., a major global telecom operator.
-
C.
Bouygues
Bouygues is a major French industrial group primarily active in construction, real estate development, media, and telecommunications.
-
D.
Free (French telecommunications company)
Free is a major French telecommunications operator known for its low-cost, disruptive internet and mobile offers that helped transform France’s telecom market.
-
E.
Dalkia
Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9868616c8190856f89fecfa1a02e |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a31600c8190a4a7ecb5231caa36 |
completed | April 4, 2026, 4:20 p.m. |
Created at: March 30, 2026, 7:58 p.m.