Triple
T34852906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1996–97 Coppa Italia |
E1004646
|
entity |
| Predicate | firstLegFinalScore |
P186367
|
FINISHED |
| Object | Vicenza 1–0 Napoli |
—
|
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: Vicenza 1–0 Napoli | Statement: [1996–97 Coppa Italia, firstLegFinalScore, Vicenza 1–0 Napoli]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLegFinalScore Context triple: [1996–97 Coppa Italia, firstLegFinalScore, Vicenza 1–0 Napoli]
-
A.
finalSecondLegScore
Indicates the score achieved in the second leg of a two-leg competition or matchup once that leg is completed.
-
B.
opponentFinalScore
Indicates the final score achieved by an opposing participant or team in a contest or game.
-
C.
finalOfficialMatchScore
Indicates the conclusive, authoritative score assigned to a match after all reviews, adjustments, or validations are completed.
-
D.
finalFirstMatchScore
chosen
Indicates the score assigned to the earliest (first) match in a sequence that is considered final or definitive for evaluation or comparison.
-
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_69f76dba76f0819090643cba102c41ec |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.