Triple
T30134184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1978 FIFA World Cup qualification |
E765939
|
entity |
| Predicate | numberOfPlacesAllocatedToEurope |
P168312
|
FINISHED |
| Object | 9.5 |
—
|
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: 9.5 | Statement: [1978 FIFA World Cup qualification, numberOfPlacesAllocatedToEurope, 9.5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlacesAllocatedToEurope Context triple: [1978 FIFA World Cup qualification, numberOfPlacesAllocatedToEurope, 9.5]
-
A.
allocatedPlacesToUEFA
chosen
Indicates that a certain number of competition places or slots have been assigned or granted to UEFA.
-
B.
representsInEurope
Indicates that an entity serves as an official representative or has representational presence within Europe.
-
C.
europeanRegion
Indicates that an entity is located in, associated with, or classified as part of a region within Europe.
-
D.
areaRankingInEurope
Indicates the position of an entity in a size-based ranking of areas within Europe.
-
E.
numberOfTripsToEurope
Indicates the count of times an entity has traveled to Europe.
- 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_6a004fd3caf48190b2ec063a7bf0756b |
completed | May 10, 2026, 9:28 a.m. |
| PD | Predicate disambiguation | batch_6a004f7672dc8190aca91d1ed855bf9a |
completed | May 10, 2026, 9:27 a.m. |
Created at: April 29, 2026, 7:16 p.m.