Triple
T15799776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NSM |
E383066
|
entity |
| Predicate | associatedCompanyFocusMarket |
P63924
|
FINISHED |
| Object | industrial applications |
—
|
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: industrial applications | Statement: [NSM, associatedCompanyFocusMarket, industrial applications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCompanyFocusMarket Context triple: [NSM, associatedCompanyFocusMarket, industrial applications]
-
A.
associatedCompanyGlobalScope
Indicates that there is a relationship linking an entity to a company at a global (worldwide) organizational scope.
-
B.
associatedCompanySpecialization
chosen
Indicates that a company is linked to a particular area of specialization or expertise.
-
C.
relatedCompanyType
Indicates the type or nature of the relationship that one company has to another company.
-
D.
acquiredCompanyFocus
Indicates that a company’s primary business focus or specialization changed as a result of acquiring another company.
-
E.
associatedCompanyBusinessSegment
Indicates that a company is linked to a specific business segment through its operations, products, or services.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4e135b08190b736e77bac5e2bff |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.