Triple
T12690271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bender family |
E303184
|
entity |
| Predicate | sectorSupported |
P32550
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [Bender family, sectorSupported, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorSupported Context triple: [Bender family, sectorSupported, education]
-
A.
sectorRecognized
Indicates that an entity has been formally acknowledged or classified within a particular sector or industry.
-
B.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
C.
sectorIncludes
Indicates that a broader sector encompasses or contains a specified sub-sector, area, or component within its scope.
-
D.
providesSupportTo
Indicates that one entity offers help, resources, or reinforcement to another entity to aid its function, stability, or success.
-
E.
sectorBenefited
chosen
Indicates that a particular sector gains advantage, support, or positive impact from a given action, policy, resource, or entity.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d962a32c6481908ddaddae4ea267bf |
completed | April 10, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69d960be63f081908a5ef5ef17a311bf |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:22 p.m.