Triple
T26152376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Census Bureau’s East North Central division |
E659862
|
entity |
| Predicate | sectorUsage |
P162915
|
FINISHED |
| Object | market research |
—
|
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: market research | Statement: [United States Census Bureau’s East North Central division, sectorUsage, market research]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorUsage Context triple: [United States Census Bureau’s East North Central division, sectorUsage, market research]
-
A.
sectorUsage
chosen
Indicates how a particular sector is utilized or engaged in a given context or activity.
-
B.
typicalSectorUse
Indicates the type of sector in which something is most commonly or characteristically used.
-
C.
capitalUse
Indicates the use or application of financial capital by one entity in relation to another entity or activity.
-
D.
gridUsage
Indicates how much and in what way an entity consumes or relies on a shared grid-based resource, such as an electrical or data grid.
-
E.
arenaUsed
Indicates that a particular arena or venue is utilized or has been employed for a specific event, activity, or purpose.
- 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_69ee5bc5a9908190899d39ce95c6d215 |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f63182f1408190bddc1214fcbd6145 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 26, 2026, 8:25 p.m.