Triple
T136542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stellantis |
E2758
|
entity |
| Predicate | hasBusinessSegment |
P1670
|
FINISHED |
| Object | automotive manufacturing |
—
|
LITERAL 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: automotive manufacturing | Statement: [Stellantis, hasBusinessSegment, automotive manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusinessSegment Context triple: [Stellantis, hasBusinessSegment, automotive manufacturing]
-
A.
operatesInSegment
chosen
Indicates that an entity conducts its activities or provides its services within a specified market or operational segment.
-
B.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
C.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
D.
hasNotableSegment
Indicates that an entity includes or contains a specific segment, part, or portion that is considered notable or significant in some way.
-
E.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
- F. None of above.
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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a4edf081908c494c8370c76b9a |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25652efdc8190b85b33735a9e6370 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.