Triple
T30016695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maccabees |
E762614
|
entity |
| Predicate | studentAthletePopulation |
P168375
|
FINISHED |
| Object | primarily Orthodox Jewish students |
—
|
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: primarily Orthodox Jewish students | Statement: [Maccabees, studentAthletePopulation, primarily Orthodox Jewish students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentAthletePopulation Context triple: [Maccabees, studentAthletePopulation, primarily Orthodox Jewish students]
-
A.
hasNumberOfStudentAthletes
Indicates the relationship that specifies how many student athletes are associated with a given entity.
-
B.
studentAthletes
Indicates a relationship where the entities are athletes who are also enrolled as students, combining academic and athletic roles.
-
C.
collegeAthleteIn
Indicates that an individual is an athlete who competes for or represents a particular college or university.
-
D.
studentPopulationLevel
Indicates the relative size or magnitude of the student population associated with an entity.
-
E.
playsIntercollegiateSport
Indicates that one entity participates as an athlete in organized sports competitions between colleges or universities.
- 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_69f2246b0c84819094f1250b6a02d277 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6798536288190bd0541e060dd9f6a |
completed | May 2, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f6749f205c81909d1aacf462912eee |
completed | May 2, 2026, 10:03 p.m. |
Created at: April 29, 2026, 6:46 p.m.