Triple
T37544461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rex Ryan’s 3–4 attacking defense |
E933419
|
entity |
| Predicate | hasLinebackerCount |
P198982
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Rex Ryan’s 3–4 attacking defense, hasLinebackerCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLinebackerCount Context triple: [Rex Ryan’s 3–4 attacking defense, hasLinebackerCount, 4]
-
A.
numberOfRunningBacks
Indicates the quantity of running backs involved or associated in the given context or situation.
-
B.
linebackersCoach
Indicates that one entity serves as the linebackers coach (position coach responsible for linebackers) for another entity, typically a team or organization.
-
C.
middleLinebacker
Indicates that one entity serves in the role of middle linebacker in relation to a football team, formation, or defensive alignment.
-
D.
defensiveLineType
Indicates the specific structural or tactical category of a defensive line used in a defensive setup or formation.
-
E.
opponentDefensiveLine
Indicates the defensive line formed by the opposing side in a competitive or adversarial context.
- 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_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff17be6ad48190963206f2619b1b28 |
completed | May 9, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69ff1724ba24819092c928fcbcb286ec |
completed | May 9, 2026, 11:14 a.m. |
| PDg | Predicate description generation | batch_69ff17bda59c8190b27c524f3e01c6df |
completed | May 9, 2026, 11:17 a.m. |
Created at: May 3, 2026, 4:17 p.m.