Triple
T11620469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Eligibility Test |
E275621
|
entity |
| Predicate | benefitOfJRF |
P487
|
FINISHED |
| Object | monthly fellowship stipend |
—
|
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: monthly fellowship stipend | Statement: [National Eligibility Test, benefitOfJRF, monthly fellowship stipend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitOfJRF Context triple: [National Eligibility Test, benefitOfJRF, monthly fellowship stipend]
-
A.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
B.
benefits
chosen
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
C.
criterionForBenefits
Indicates that something serves as a condition or standard that must be met in order for an entity to receive certain benefits.
-
D.
benefitForFaculty
Indicates that something provides an advantage, support, or positive outcome specifically for faculty members.
-
E.
benefitsCause
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or cause.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a1206f1c81908d92024ef71958c0 |
completed | April 10, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69d85dd6503c819081f9045e9d5c4f3f |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:39 p.m.