Triple
T29290168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentina vs Croatia (2018 FIFA World Cup Group D) |
E742638
|
entity |
| Predicate | RebicGoalMinute |
P82465
|
FINISHED |
| Object | 53 |
—
|
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: 53 | Statement: [Argentina vs Croatia (2018 FIFA World Cup Group D), RebicGoalMinute, 53]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RebicGoalMinute Context triple: [Argentina vs Croatia (2018 FIFA World Cup Group D), RebicGoalMinute, 53]
-
A.
minuteOfGoal
chosen
Indicates the specific minute in a match when a particular goal was scored.
-
B.
fastestGoalTime
Indicates the shortest amount of time taken by an entity to achieve a specified goal or outcome.
-
C.
goalTimeRecord
Indicates that a specific time value is recorded as the target or goal duration for an activity or process.
-
D.
minuteOfOpeningGoal
Indicates the specific minute in a match when the first (opening) goal is scored.
-
E.
totalGoalsRecord
Indicates the total number of goals that have been recorded for an entity across all relevant events or contexts.
- 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_69f0912323c48190b9a24ef8cf359225 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6653fd31c8190af982a019dfe645e |
completed | May 2, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 1:01 p.m.