Triple
T6232435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expo '70 |
E139387
|
entity |
| Predicate | numberOfCorporatePavilions |
P19114
|
FINISHED |
| Object | over 30 |
—
|
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: over 30 | Statement: [Expo '70, numberOfCorporatePavilions, over 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCorporatePavilions Context triple: [Expo '70, numberOfCorporatePavilions, over 30]
-
A.
numberOfPavilions
chosen
Indicates the total count of pavilions associated with a given entity or context.
-
B.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
C.
hasPavilion
Indicates that one entity possesses, includes, or is associated with a pavilion as part of its structure, property, or facilities.
-
D.
numberOfHalls
Indicates the quantity of halls associated with a given entity or location.
-
E.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
- 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062ee6f088190bf72692eb8ffb761 |
completed | March 22, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69c05601de6481909d0880048fd7b49a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:22 p.m.