Triple
T6547464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liguilla |
E151045
|
entity |
| Predicate | tieBreakingRulesInclude |
P6631
|
FINISHED |
| Object | aggregate score |
—
|
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: aggregate score | Statement: [Liguilla, tieBreakingRulesInclude, aggregate score]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieBreakingRulesInclude Context triple: [Liguilla, tieBreakingRulesInclude, aggregate score]
-
A.
tiebreaker
chosen
Indicates that one entity serves as the deciding factor used to break a tie between two or more otherwise equal options or outcomes.
-
B.
eligibilityRulesSetBy
Indicates that one party defines or establishes the criteria or rules determining another party’s eligibility for something.
-
C.
tieAllowedAfterRegulation
Indicates that a tie outcome is permitted to occur after the application or completion of a specified regulation or regulatory process.
-
D.
hasSpecialRules
Indicates that certain entities are governed by additional or exceptional rules that differ from the standard ones.
-
E.
breaksWith
Indicates that one entity ends or disrupts an existing association, agreement, or alignment with another entity.
- 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_69c687f3fd60819083bfa583e5bcfa71 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce07332481909a5a7964282eb776 |
completed | March 27, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69c6acf3e3708190b052ec774e607cb7 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:50 p.m.