Triple
T29710421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Korea vs Mexico (2018 FIFA World Cup) |
E751762
|
entity |
| Predicate | penaltyAwardedToTeam |
P168777
|
FINISHED |
| Object | Mexico national football team |
—
|
NE NERFINISHED |
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: Mexico national football team | Statement: [South Korea vs Mexico (2018 FIFA World Cup), penaltyAwardedToTeam, Mexico national football team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: penaltyAwardedToTeam Context triple: [South Korea vs Mexico (2018 FIFA World Cup), penaltyAwardedToTeam, Mexico national football team]
-
A.
penaltyScoredBy
Indicates that a penalty (typically in a game or sport) was successfully converted or scored by a particular participant.
-
B.
fairPlayAwardTeam
Indicates that a team has been recognized with a fair play award for exemplary sportsmanship or ethical conduct in competition.
-
C.
penaltyGoalPoints
Indicates that points are awarded for a goal scored from a penalty situation.
-
D.
finalScorePenalties
Indicates the penalties that are applied to determine or adjust the final score in a given context.
-
E.
penaltyFrom7thFoul
Indicates that a penalty situation arises as a result of committing a seventh foul.
- 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_69f0d62748848190b030d0a703629a7d |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67805551c81909e016ae9e3031076 |
completed | May 2, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676f73c3481909f01fa69851b7298 |
completed | May 2, 2026, 10:13 p.m. |
Created at: April 28, 2026, 7:30 p.m.