Triple
T4748935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PRESIDENT'S HUNDRED |
E105429
|
entity |
| Predicate | minimumRankEligible |
P16384
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [PRESIDENT'S HUNDRED, minimumRankEligible, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumRankEligible Context triple: [PRESIDENT'S HUNDRED, minimumRankEligible, 1]
-
A.
eligibleRank
chosen
Indicates that an entity meets the required rank or level criteria to qualify for a specific role, action, or benefit.
-
B.
rankRestriction
Indicates a constraint or limit placed on the rank or hierarchical level that an entity may hold within a given system or structure.
-
C.
eligibilityLevel
Indicates the degree or tier of qualification an entity has for a given benefit, service, or status.
-
D.
requiresMinimumScore
Indicates that one entity can only be obtained, accessed, or considered valid if another entity’s score meets or exceeds a specified minimum threshold.
-
E.
lowestRank
Indicates that the subject has the least or worst rank in an ordered set compared to all other related entities.
- 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_69bd43f07fa48190954317d01600994a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64c6f5ac81908a62f9c17e77ac86 |
completed | March 20, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69bd6223defc8190823665a6592c1154 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.