Triple
T2649930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1970 FIFA World Cup |
E53871
|
entity |
| Predicate | qualificationSpots |
P30746
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [1970 FIFA World Cup, qualificationSpots, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: qualificationSpots Context triple: [1970 FIFA World Cup, qualificationSpots, 14]
-
A.
qualificationSpotAllocation
chosen
Indicates the assignment of available qualification spots or slots to entities based on predefined criteria or results.
-
B.
typicalConferenceLeagueSpots
Indicates the usual number of qualification spots a league provides for the UEFA Europa Conference League based on its standard allocation rules.
-
C.
qualifyingEvent
Indicates that an event meets specific conditions or criteria that make an entity eligible for a particular status, action, or outcome.
-
D.
teamEligibility
Indicates whether an entity meets the required conditions to participate as a member of a particular team.
-
E.
numberOfStandingPlaces
Indicates the total count of standing-only positions or spots available in a given context (e.g., a vehicle, venue, or area).
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd91ca1288190ba302b04bac4c153 |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd814298c8190952f05aed43f6bb8 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.