Triple
T3832488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armand Peugeot |
E91044
|
entity |
| Predicate | industryTransformedInto |
P45320
|
FINISHED |
| Object | automobile manufacturing company |
—
|
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: automobile manufacturing company | Statement: [Armand Peugeot, industryTransformedInto, automobile manufacturing company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industryTransformedInto Context triple: [Armand Peugeot, industryTransformedInto, automobile manufacturing company]
-
A.
industryTransformed
chosen
Indicates that an entity has fundamentally changed the structure, practices, or dynamics of a particular industry.
-
B.
corporateTransformation
Indicates a relationship where an organization undergoes a significant structural, strategic, or operational change from one corporate state to another.
-
C.
industryContext
Indicates the industry or sector within which an entity, activity, or relationship is situated or most relevant.
-
D.
technologyTransition
Indicates a change in the primary technology, method, or system used from one technological state or solution to another.
-
E.
industryCenter
Indicates that a location functions as a primary hub or focal point for industrial activity or production.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8787bc8190819a7af975b609df |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.