Triple
T29872995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1962 FIFA World Cup qualification |
E758643
|
entity |
| Predicate | numberOfTeamsEntered |
P6986
|
FINISHED |
| Object | 56 |
—
|
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: 56 | Statement: [1962 FIFA World Cup qualification, numberOfTeamsEntered, 56]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTeamsEntered Context triple: [1962 FIFA World Cup qualification, numberOfTeamsEntered, 56]
-
A.
hasNumberOfTeams
chosen
Indicates the quantity of teams associated with or contained by a given entity.
-
B.
numberOfOpenDivisionTeamsEntered
Indicates the quantity of teams that have been entered into an open division.
-
C.
qualifiedTeamsCount
Indicates the number of teams that have successfully met the criteria to qualify for a given stage, event, or competition.
-
D.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
E.
numberOfTeamsLater
Indicates that one entity has a greater number of teams than another entity at a later point in time.
- 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a001cc0ff588190bb7c8a6fd427d02b |
completed | May 10, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_6a001b3ea18c8190aeda7a32b2697490 |
completed | May 10, 2026, 5:44 a.m. |
Created at: April 29, 2026, 5:54 p.m.