Triple
T488546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darrell Green |
E9933
|
entity |
| Predicate | playedCareerEnd |
P8357
|
FINISHED |
| Object | 2002 |
—
|
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: 2002 | Statement: [Darrell Green, playedCareerEnd, 2002]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedCareerEnd Context triple: [Darrell Green, playedCareerEnd, 2002]
-
A.
retiredFrom
Indicates that an entity has permanently stopped working for or being active in a specified organization, role, or activity.
-
B.
activeYearsInSport
chosen
Indicates the span of years during which an entity actively participated in a particular sport.
-
C.
careerLosses
Indicates the total number of defeats or losses an entity has accumulated over the course of its entire career.
-
D.
playedFor
Indicates that one entity has been a member of or participated as a player for a particular team, organization, or group.
-
E.
careerRuns
Indicates the total number of runs a player has scored over the entire duration of their professional career.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0df764481909811d9483dfbc4aa |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf63fbc819090ea6ca11f39116a |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.