Triple
T11075237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hochtief |
E261848
|
entity |
| Predicate | hasCompetitor |
P1375
|
FINISHED |
| Object | Bouygues |
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 | Statement: [Hochtief, hasCompetitor, Bouygues]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bouygues Context triple: [Hochtief, hasCompetitor, Bouygues]
-
A.
Bouygues
chosen
Bouygues is a major French industrial group primarily active in construction, real estate development, media, and telecommunications.
-
B.
Eiffage
Eiffage is a major French construction and civil engineering company known for delivering large-scale infrastructure projects such as the Millau Viaduct.
-
C.
Dalkia
Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
-
D.
France Télécom
France Télécom was the former state-owned French telecommunications company that evolved into Orange S.A., a major global telecom operator.
-
E.
GDF Suez
GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7994efb608190a81bc8c4d16ddbd0 |
completed | April 9, 2026, 12:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c8cc77988190aad54f56dbd0f8cf |
completed | April 18, 2026, 6:09 p.m. |
Created at: April 8, 2026, 9:26 p.m.