Triple
T24395140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Labor Relations Board v. Friedman-Harry Marks Clothing Co. |
E615007
|
entity |
| Predicate | respondentIndustry |
P156040
|
FINISHED |
| Object | clothing manufacturing |
—
|
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: clothing manufacturing | Statement: [National Labor Relations Board v. Friedman-Harry Marks Clothing Co., respondentIndustry, clothing manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: respondentIndustry Context triple: [National Labor Relations Board v. Friedman-Harry Marks Clothing Co., respondentIndustry, clothing manufacturing]
-
A.
respondentBusiness
Indicates that a business entity is the one providing answers or participating as the responding party in a survey, form, or legal/administrative process.
-
B.
industryResponseTo
Indicates that an industry reacts or responds in some way to a particular event, condition, policy, or influence.
-
C.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
D.
occupantIndustry
Indicates the industry or sector in which an occupant (such as a tenant or user of a space) operates.
-
E.
targetCompanyIndustry
Indicates that a company operates within or is associated with a specified industry sector.
- 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_69e2d7e509b88190a53155d4f3de45ce |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294d69b5c81908cf6143374934f5c |
completed | April 29, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:04 a.m.