Triple
T2453955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jared Goff |
E53772
|
entity |
| Predicate | collegeMajor |
P39964
|
FINISHED |
| Object | sociology (reported) |
—
|
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: sociology (reported) | Statement: [Jared Goff, collegeMajor, sociology (reported)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeMajor Context triple: [Jared Goff, collegeMajor, sociology (reported)]
-
A.
otherMajors
Indicates that an entity has additional academic majors beyond its primary or currently referenced major.
-
B.
college
Indicates that an entity is a college-level educational institution attended by or associated with another entity.
-
C.
collegePosition
Indicates the role, title, or position an individual holds within a college or university.
-
D.
offersFieldOfStudy
Indicates that an institution or program provides a particular field of study as an available area of academic focus.
-
E.
university
Indicates that an educational institution of higher learning is associated with or attended by a given 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_69ab495d227c8190b26ae6548eeb1019 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0aed2688190a18fe66b98d80e0b |
completed | March 7, 2026, 7:15 a.m. |
| PDg | Predicate description generation | batch_69abd2baee308190bdaa41ef1f6bc9cc |
completed | March 7, 2026, 7:24 a.m. |
Created at: March 6, 2026, 9:44 p.m.