Triple
T1202608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detroit metropolitan area |
E25816
|
entity |
| Predicate | centerOfIndustry |
P3436
|
FINISHED |
| Object | automotive industry |
—
|
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 industry | Statement: [Detroit metropolitan area, centerOfIndustry, automotive industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centerOfIndustry Context triple: [Detroit metropolitan area, centerOfIndustry, automotive industry]
-
A.
industryCenter
Indicates that a location functions as a primary hub or focal point for industrial activity or production.
-
B.
isIndustrialCenter
chosen
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
-
C.
industryConsortium
Indicates a collaborative association where multiple organizations formally join together within an industry to pursue shared goals, standards, or initiatives.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
foundingIndustry
Indicates the industry or sector in which an entity was originally founded or began its primary operations.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdbda0b081909c0147121a945e27 |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.