Triple
T29649575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poland vs Senegal (2018 FIFA World Cup) |
E756097
|
entity |
| Predicate | thirdGoalMinute |
P82465
|
FINISHED |
| Object | 86 |
—
|
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: 86 | Statement: [Poland vs Senegal (2018 FIFA World Cup), thirdGoalMinute, 86]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdGoalMinute Context triple: [Poland vs Senegal (2018 FIFA World Cup), thirdGoalMinute, 86]
-
A.
minuteOfGoal
chosen
Indicates the specific minute in a match when a particular goal was scored.
-
B.
minuteOfOpeningGoal
Indicates the specific minute in a match when the first (opening) goal is scored.
-
C.
targetScoreAfterThreeQuarters
Indicates the score that a target entity has accumulated by the end of the third quarter of a game or timed event.
-
D.
decidingGoalMinute
Indicates the minute in a match when a goal is scored that ultimately decides the outcome (e.g., the winning or decisive goal).
-
E.
fastestGoalTime
Indicates the shortest amount of time taken by an entity to achieve a specified goal or outcome.
- 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_69f0ef89d2c88190a6d0d5116ccd7cc9 |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 28, 2026, 6:51 p.m.