Triple
T35808856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punt Kick |
E1035173
|
entity |
| Predicate | requiresPrecision |
P9771
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Punt Kick, requiresPrecision, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresPrecision Context triple: [Punt Kick, requiresPrecision, yes]
-
A.
supportsPrecisionLevels
Indicates that one entity is capable of operating at, or accommodating, multiple specified levels of precision in relation to another entity or process.
-
B.
precision
chosen
Indicates the degree to which an action, measurement, or outcome is carried out with exactness, minimal deviation, and fine-grained accuracy.
-
C.
hasCoordinatePrecision
Indicates the degree of exactness or granularity with which an entity’s spatial coordinates are specified.
-
D.
requiresMeasures
Indicates that one entity necessitates the implementation or presence of specific measures, actions, or safeguards in relation to another entity or situation.
-
E.
exactFor
Indicates that one entity corresponds to or matches another entity with complete precision, without any deviation or approximation.
- 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_69f76e1762408190b885a8456862e372 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffc516d1908190b475f5a6156b0ca8 |
completed | May 9, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69ffc4a946e08190b3535a5dc15ac484 |
completed | May 9, 2026, 11:35 p.m. |
Created at: May 3, 2026, 4:06 p.m.