Triple
T38598277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1986 World Exposition on Transportation and Communication |
E934140
|
entity |
| Predicate | countryParticipantsCount |
P56465
|
FINISHED |
| Object | over 50 |
—
|
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 50 | Statement: [1986 World Exposition on Transportation and Communication, countryParticipantsCount, over 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryParticipantsCount Context triple: [1986 World Exposition on Transportation and Communication, countryParticipantsCount, over 50]
-
A.
countryParticipation
Indicates that a country takes part in, is involved with, or contributes to a particular event, activity, agreement, or organization.
-
B.
countryRepresentedCount
chosen
Indicates the number of distinct countries that are represented or associated with a given entity.
-
C.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
D.
countryMembers
Indicates that certain entities are members or constituent parts of a specified country.
-
E.
countryRepresented
Indicates that one entity serves as the official representative (such as an athlete, diplomat, or delegate) of a specific country in a given context or event.
- 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_69f76ecc17688190b389b693a5927501 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.