Triple
T423223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl LIII |
E8149
|
entity |
| Predicate | losingScore |
P7493
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Super Bowl LIII, losingScore, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: losingScore Context triple: [Super Bowl LIII, losingScore, 3]
-
A.
loserScore
chosen
Indicates the number of points or score achieved by the losing participant in a competitive event or comparison.
-
B.
loserPoints
Indicates the number of points awarded to or accumulated by the losing side in a competitive event or comparison.
-
C.
loserParty
Indicates that a particular political party was the one that lost in a given election or contest.
-
D.
losingManager
Indicates that the referenced manager is the one whose team or organization was defeated or performed worse in a particular competition, comparison, or event.
-
E.
finalScore
Indicates the resulting or overall score achieved after all contributing actions, events, or evaluations are completed.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eec200648190bcb9f1b98c8e9cdf |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd5439c8190aea661b8b4aa51e9 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.