Triple
T5772158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 FIFA World Cup |
E127353
|
entity |
| Predicate | continentHostingGapSincePreviousInContinent |
P66334
|
FINISHED |
| Object | 36 years |
—
|
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: 36 years | Statement: [2014 FIFA World Cup, continentHostingGapSincePreviousInContinent, 36 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: continentHostingGapSincePreviousInContinent Context triple: [2014 FIFA World Cup, continentHostingGapSincePreviousInContinent, 36 years]
-
A.
continentType
Indicates that one entity is classified as a specific type or category of continent in relation to another entity.
-
B.
closestDistanceBetweenContinents
Indicates the minimum geographical distance separating any points on two different continents.
-
C.
visitedContinent
Indicates that an entity has traveled to and spent time on a particular continent.
-
D.
continentB
Indicates that the subject entity is a continent that contains or is associated with the object entity (such as a country, region, or location).
-
E.
continentScope
Indicates that something applies within, is limited to, or is defined at the level of a specific continent.
- F. None of above. chosen
Provenance (4 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_69c00834f6308190851b0abeddd8ed7e |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021d0c6088190ba670ddcdbf5ca3e |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c02ac9603481909e3fa295d7904a15 |
completed | March 22, 2026, 5:45 p.m. |
Created at: March 22, 2026, 3:50 p.m.