Triple
T25579495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Automobile City |
E641200
|
entity |
| Predicate | sectorDominance |
P67914
|
FINISHED |
| Object | automotive manufacturing in local economy |
—
|
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 in local economy | Statement: [Automobile City, sectorDominance, automotive manufacturing in local economy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorDominance Context triple: [Automobile City, sectorDominance, automotive manufacturing in local economy]
-
A.
sectorInfluence
Indicates the degree to which one sector affects, shapes, or exerts control over another sector or over outcomes within that sector.
-
B.
sectorStrength
Indicates the relative performance or influence level of a specific sector compared to others within a broader system or market.
-
C.
dominatedSector
chosen
Indicates that one entity exercises prevailing control or influence over a particular sector relative to others.
-
D.
peakMarketShare
Indicates the highest proportion of total market sales or customers that an entity has achieved over a specified period.
-
E.
industryExposure
Indicates the extent to which an entity is involved in, affected by, or financially linked to a particular industry or set of industries.
- 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_69e75dc281bc819095ec04dc0c3a94d0 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f93364308190bcffdb00ee0ec6c7 |
completed | May 2, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69f5afec3e94819080d9ba86cf8c866e |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 4:04 p.m.