Triple
T20607173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gino Torretta |
E506338
|
entity |
| Predicate | collegeCareerStartYear |
P43469
|
FINISHED |
| Object | 1989 |
—
|
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: 1989 | Statement: [Gino Torretta, collegeCareerStartYear, 1989]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeCareerStartYear Context triple: [Gino Torretta, collegeCareerStartYear, 1989]
-
A.
studCareerStartYear
Indicates the calendar year in which a student's academic or educational career formally began.
-
B.
collegeCareerPeriod
Indicates the time span during which an individual is engaged in their college or university education and related academic activities.
-
C.
collegeCareerStart
chosen
Indicates the time or event at which an individual begins their college-level academic career.
-
D.
collegeCareerPoints
Indicates the total number of points an individual scored over the course of their college playing career.
-
E.
studCareerBegan
Indicates that a student's professional or academic career started at a specified time or institution.
- 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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aad394e8819080185187a8b3de93 |
completed | April 20, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.