Triple
T22503806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EXALEAD |
E556338
|
entity |
| Predicate | formerDeveloper |
P22674
|
FINISHED |
| Object | EXALEAD S.A. |
—
|
NE NERFINISHED |
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: EXALEAD S.A. | Statement: [EXALEAD, formerDeveloper, EXALEAD S.A.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EXALEAD S.A. Context triple: [EXALEAD, formerDeveloper, EXALEAD S.A.]
-
A.
EXALEAD
chosen
EXALEAD is an enterprise search and information access software brand known for its advanced search, indexing, and data discovery solutions.
-
B.
Adevinta
Adevinta is a global online classifieds company that operates digital marketplaces for buying and selling goods, services, and real estate across multiple countries.
-
C.
Groupe GTM
Groupe GTM was a major French construction and civil engineering company that later became part of the Vinci SA group.
-
D.
Acxiom
Acxiom is a global data and marketing technology company known for providing consumer data, analytics, and audience targeting solutions to businesses.
-
E.
Amadeus IT Group
Amadeus IT Group is a leading global travel technology company that provides reservation, distribution, and IT solutions for airlines, travel agencies, hotels, and other travel industry players.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5ac5808190a66f9111c350f4dc |
completed | April 29, 2026, 1:22 a.m. |
Created at: April 16, 2026, 8:50 p.m.