Triple
T4351652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opportunity (Expo 2020 subtheme) |
E98038
|
entity |
| Predicate | hasPavilionFunction |
P55703
|
FINISHED |
| Object | showcase initiatives that unlock human potential |
—
|
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: showcase initiatives that unlock human potential | Statement: [Opportunity (Expo 2020 subtheme), hasPavilionFunction, showcase initiatives that unlock human potential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPavilionFunction Context triple: [Opportunity (Expo 2020 subtheme), hasPavilionFunction, showcase initiatives that unlock human potential]
-
A.
hasPavilion
Indicates that one entity possesses, includes, or is associated with a pavilion as part of its structure, property, or facilities.
-
B.
hasMuseumFunction
Indicates that an entity serves the role or performs the function of a museum.
-
C.
hasFoyer
Indicates that an entity includes or is equipped with a foyer as part of its structure or layout.
-
D.
numberOfPavilions
Indicates the total count of pavilions associated with a given entity or context.
-
E.
hasParkFeature
Indicates that a park includes, contains, or is associated with a specific feature or amenity.
- 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351a99788819080b13a20124e49a0 |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f51ed7c8190b7bf5f44b56b730d |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:15 p.m.