Triple
T23018631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TEACH Grant Program |
E573102
|
entity |
| Predicate | highNeedFieldExample |
P150697
|
FINISHED |
| Object | mathematics |
—
|
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: mathematics | Statement: [TEACH Grant Program, highNeedFieldExample, mathematics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highNeedFieldExample Context triple: [TEACH Grant Program, highNeedFieldExample, mathematics]
-
A.
recognizedNeedFor
Indicates that one entity has identified or acknowledged the necessity or requirement for another entity or condition.
-
B.
needBased
Indicates that something is determined, allocated, or provided according to the level of need rather than uniform or fixed criteria.
-
C.
meetsNeedOf
Indicates that one entity sufficiently fulfills or satisfies the requirement, demand, or expectation specified by another entity.
-
D.
extraExample
Indicates that something is provided as an additional, illustrative instance beyond the main or required examples.
-
E.
holderField
Indicates that a specified field or attribute belongs to, is maintained by, or is associated with a particular holder entity.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e777cc81908c0b0bfd9d5a717c |
completed | April 29, 2026, 4:07 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
| PDg | Predicate description generation | batch_69ef538b29c081908fa56ee35a1dcee7 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:52 p.m.