Triple
T2492661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Better Make Room |
E52079
|
entity |
| Predicate | operatesWithinSector |
P2193
|
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: [Better Make Room, operatesWithinSector, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesWithinSector Context triple: [Better Make Room, operatesWithinSector, education]
-
A.
operatesWithin
Indicates that one entity carries out its activities, functions, or operations inside the scope, boundaries, or jurisdiction defined by another entity.
-
B.
operatesInSegment
Indicates that an entity conducts its activities or provides its services within a specified market or operational segment.
-
C.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
-
D.
sectorServed
chosen
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
E.
alsoOperatesIn
Indicates that an entity, in addition to its primary location or domain, conducts operations or activities in another specified place or context.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd192cad08190b13bf8e2d7149199 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.