Triple
T19915202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inuksuit |
E478646
|
entity |
| Predicate | typicalPerformerCount |
P137796
|
FINISHED |
| Object | 9 to 99 percussionists |
—
|
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: 9 to 99 percussionists | Statement: [Inuksuit, typicalPerformerCount, 9 to 99 percussionists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPerformerCount Context triple: [Inuksuit, typicalPerformerCount, 9 to 99 percussionists]
-
A.
numberOfPerformers
Indicates the quantity of performers involved in a given event, act, or performance.
-
B.
typicalPerformers
Indicates the entities that most commonly or characteristically perform a given action or role.
-
C.
numberOfMainPerformers
Indicates the count of primary performers involved in a performance or event.
-
D.
typicalNumberOfDancers
Indicates the usual or standard number of dancers involved in a particular dance, performance, or context.
-
E.
typicalPerformance
Indicates the usual or characteristic level at which an entity performs under normal conditions.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6599394f081909246006c2e83bacc |
completed | April 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:53 p.m.