Triple
T488555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darrell Green |
E9933
|
entity |
| Predicate | interceptions |
P14052
|
FINISHED |
| Object | 54 |
—
|
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: 54 | Statement: [Darrell Green, interceptions, 54]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interceptions Context triple: [Darrell Green, interceptions, 54]
-
A.
interceptedQuarterback
Indicates that a defensive player successfully caught a pass thrown by the quarterback, resulting in an interception.
-
B.
catches
Indicates that one entity successfully seizes, intercepts, or takes hold of another entity, often stopping its motion or preventing its escape.
-
C.
interceptionYardLine
Indicates the yard line on the field where an interception occurs during a play.
-
D.
interceptingPlayer
Indicates that one player takes possession of or disrupts a pass, throw, or transmission intended for another player or target.
-
E.
intervenedIn
Indicates that an entity took action to alter, influence, or interrupt the course of an event, process, or interaction involving other entities.
- 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_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. |
| PDg | Predicate description generation | batch_69a2eebb2c908190960a4d0c014304cd |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.