Triple
T13615350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NAICS codes |
E325296
|
entity |
| Predicate | exampleSector |
P71
|
FINISHED |
| Object | 11 Agriculture, Forestry, Fishing and Hunting |
—
|
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: 11 Agriculture, Forestry, Fishing and Hunting | Statement: [NAICS codes, exampleSector, 11 Agriculture, Forestry, Fishing and Hunting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleSector Context triple: [NAICS codes, exampleSector, 11 Agriculture, Forestry, Fishing and Hunting]
-
A.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
B.
sectorOfOperation
Indicates the industry, domain, or field within which an entity conducts its primary activities or operations.
-
C.
sector
chosen
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
D.
targetsSector
Indicates that an entity is directed toward, focused on, or intended to affect a particular economic or industry sector.
-
E.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.