Triple
T853934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations Human Rights Council |
E18447
|
entity |
| Predicate | numberOfRegularSessionsPerYear |
P6891
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [United Nations Human Rights Council, numberOfRegularSessionsPerYear, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRegularSessionsPerYear Context triple: [United Nations Human Rights Council, numberOfRegularSessionsPerYear, 3]
-
A.
typicalNumberOfMeetingsPerSeason
Indicates the usual or average count of meetings that occur within a single season.
-
B.
hasLegislativeSessionCount
Indicates the number of legislative sessions associated with a given legislative body, term, or jurisdiction.
-
C.
meetsBetweenSessionsOf
Indicates that one entity meets another during the interval between scheduled sessions or events.
-
D.
convenesRegularSession
Indicates that an entity formally brings together a group or body for its routine or scheduled meeting.
-
E.
sessionCount
chosen
Indicates the number of distinct sessions associated with an entity or interaction 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_69a4938bdd3c8190a954a3c11844d9cf |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac389a44819093396a58d2afa700 |
completed | March 1, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69a4aa81ef348190b067f817574e9efe |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.