Triple
T30134188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1978 FIFA World Cup qualification |
E765939
|
entity |
| Predicate | numberOfPlacesAllocatedToAsiaAndOceania |
P76381
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [1978 FIFA World Cup qualification, numberOfPlacesAllocatedToAsiaAndOceania, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlacesAllocatedToAsiaAndOceania Context triple: [1978 FIFA World Cup qualification, numberOfPlacesAllocatedToAsiaAndOceania, 1]
-
A.
numberOfQualifiedTeamsFromAsiaOceania
Indicates the count of teams from the Asia-Oceania region that meet the specified qualification criteria.
-
B.
locatedInAsia
Indicates that the subject entity is geographically situated within the continent of Asia.
-
C.
locatedInOceania
Indicates that one entity is geographically situated within the region of Oceania.
-
D.
representsInAsia
Indicates that the subject entity is located within or associated with the geographic region of Asia.
-
E.
regionSeatsCount
chosen
Indicates the number of seats allocated or available within a specific region.
- 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_69f22477d1a081908df2b7e6ed16859d |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a0056174c908190be99c91a70393e47 |
completed | May 10, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_6a00538e7e08819091ecd4316cd641a1 |
completed | May 10, 2026, 9:44 a.m. |
Created at: April 29, 2026, 7:16 p.m.