Triple
T35876899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emilio Bombassei |
E1037390
|
entity |
| Predicate | associatedIndustrySegment |
P206086
|
FINISHED |
| Object | original equipment manufacturer (OEM) braking systems |
—
|
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: original equipment manufacturer (OEM) braking systems | Statement: [Emilio Bombassei, associatedIndustrySegment, original equipment manufacturer (OEM) braking systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedIndustrySegment Context triple: [Emilio Bombassei, associatedIndustrySegment, original equipment manufacturer (OEM) braking systems]
-
A.
associatedCompanyBusinessSegment
Indicates that a company is linked to a specific business segment through its operations, products, or services.
-
B.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
C.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
D.
possibleIndustry
Indicates a potential or likely industry with which an entity may be associated or classified.
-
E.
supportedIndustry
Indicates that one entity provides backing, resources, or services to help sustain or advance a particular industry.
- F. None of above. chosen
Provenance (4 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_69f76e1e701c8190a4990d4978ce4fe6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037ce53de881908cf14141cf3bc570 |
completed | May 12, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:06 p.m.