Triple
T12829777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goal of the Century |
E306752
|
entity |
| Predicate | numberOfOpponentsBeaten |
P107109
|
FINISHED |
| Object | five outfield players plus goalkeeper |
—
|
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: five outfield players plus goalkeeper | Statement: [Goal of the Century, numberOfOpponentsBeaten, five outfield players plus goalkeeper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfOpponentsBeaten Context triple: [Goal of the Century, numberOfOpponentsBeaten, five outfield players plus goalkeeper]
-
A.
numberOfWins
Indicates the count of times an entity has achieved victory in a relevant context or competition.
-
B.
wonAgainst
Indicates that one entity achieved victory over another in a competition, conflict, or contest.
-
C.
opponentStrength
Indicates the level or degree of power, skill, or capability possessed by an opposing party in a competitive or adversarial context.
-
D.
wasOpponentOf
Indicates that one entity competed or conflicted against another as an adversary in some contest, game, or confrontation.
-
E.
careerWins
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
- F. None of above. chosen
Provenance (4 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:34 p.m.