Triple
T36917116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia vs Texas Tech |
E913072
|
entity |
| Predicate | VirginiaRegulationScore |
P124163
|
FINISHED |
| Object | 68 |
—
|
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: 68 | Statement: [Virginia vs Texas Tech, VirginiaRegulationScore, 68]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: VirginiaRegulationScore Context triple: [Virginia vs Texas Tech, VirginiaRegulationScore, 68]
-
A.
regulationScore
Indicates the degree or quality of how well something is controlled, managed, or kept within desired limits.
-
B.
jurisdictionSpecificScore
chosen
Indicates a score or rating that is calculated specifically for, and applicable within, a particular legal or geographic jurisdiction.
-
C.
displayRegulation
Indicates that an entity presents or shows a regulation or set of rules, making it visible or accessible to others.
-
D.
regulationStatus
Indicates the regulatory condition or compliance state that applies to an entity under relevant rules or laws.
-
E.
regulationAtIssue
Indicates that a specific regulation is the subject of concern, dispute, or analysis in the given context.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:13 p.m.