Triple
T29989043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hubert & Folsom |
E761818
|
entity |
| Predicate | possibleIndustry |
P174297
|
FINISHED |
| Object | law |
—
|
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: law | Statement: [Hubert & Folsom, possibleIndustry, law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possibleIndustry Context triple: [Hubert & Folsom, possibleIndustry, law]
-
A.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
B.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
C.
employmentBasedCategory
Indicates that one entity’s classification or status is determined by its relationship to employment, such as being based on a specific job, role, or work-related category.
-
D.
targetIndustryDepicted
Indicates that an entity visually represents or portrays a specific industry as its primary subject or focus.
-
E.
industryActivities
Indicates the types of economic or business activities in which an industry or sector is engaged.
- 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_69f224695498819094a81037cad401e2 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69f6bbf5a8288190ae170bcbe8ab65cf |
completed | May 3, 2026, 3:07 a.m. |
Created at: April 29, 2026, 6:37 p.m.