Triple
T30377857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Gipp |
E772739
|
entity |
| Predicate | playedYears |
P67438
|
FINISHED |
| Object | 1917 |
—
|
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: 1917 | Statement: [George Gipp, playedYears, 1917]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedYears Context triple: [George Gipp, playedYears, 1917]
-
A.
activeYearsInCareer
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
-
B.
activeYearsInSport
Indicates the span of years during which an entity actively participated in a particular sport.
-
C.
competitionYears
Indicates the years during which the entities were involved in a particular competition or competitive event.
-
D.
seasonYears
Indicates the span of calendar years during which a particular season (e.g., of a show, competition, or activity) takes place or is valid.
-
E.
playedCareerStartYear
chosen
Indicates the calendar year in which an entity’s playing career (such as a professional or competitive role) began.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 29, 2026, 8 p.m.