Triple
T15292357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VAL |
E365558
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Matra Transport |
E857763
|
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: Matra Transport | Statement: [VAL, developer, Matra Transport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matra Transport Context triple: [VAL, developer, Matra Transport]
-
A.
Matra Automobiles
chosen
Matra Automobiles was a French car manufacturer best known for its innovative sports cars and collaborations with brands like Renault and Simca during the late 20th century.
-
B.
Traton
Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
-
C.
Peugeot
Peugeot is a historic French automobile manufacturer known for producing a wide range of passenger cars and commercial vehicles, now operating as a core brand within the multinational automotive group Stellantis.
-
D.
Renault Trucks
Renault Trucks is a French commercial vehicle manufacturer known for producing a wide range of trucks and heavy-duty vehicles for distribution, construction, and long-haul transport.
-
E.
Renault
Renault is a major French automobile manufacturer known for producing a wide range of passenger cars, commercial vehicles, and electric vehicles sold worldwide.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03680b60c8190a3ea54a9d34c8105 |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef7f2fc08190937226dad5fdc9c6 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:15 a.m.