Triple
T23018630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TEACH Grant Program |
E573102
|
entity |
| Predicate | targetSchoolCharacteristic |
P72238
|
FINISHED |
| Object | low-income school |
—
|
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: low-income school | Statement: [TEACH Grant Program, targetSchoolCharacteristic, low-income school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetSchoolCharacteristic Context triple: [TEACH Grant Program, targetSchoolCharacteristic, low-income school]
-
A.
educationSystemCharacteristic
Indicates a characteristic, feature, or attribute that describes an education system.
-
B.
schoolClassification
chosen
Indicates how a school is categorized within an educational system, such as by level, type, or other official classification.
-
C.
attendsSchoolIn
Indicates that a person is enrolled as a student at, and regularly goes to, a school located in a particular place.
-
D.
educationLevelCharacteristic
Indicates that one entity specifies, describes, or constrains the education level associated with another entity.
-
E.
educationFacility
Indicates that one entity functions as an institution or place where the other entity receives or provides education or training.
- 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_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. |
Created at: April 17, 2026, 3:52 p.m.