Triple
T5320827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prima Donna |
E121666
|
entity |
| Predicate | hasInterval |
P63472
|
FINISHED |
| Object | one intermission |
—
|
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: one intermission | Statement: [Prima Donna, hasInterval, one intermission]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInterval Context triple: [Prima Donna, hasInterval, one intermission]
-
A.
intervalAct
Indicates an action or relationship that occurs over, or is defined by, a specific time interval between entities.
-
B.
hasTimer
Indicates that an entity is associated with or controlled by a timer mechanism that measures or limits a duration or interval.
-
C.
hasCountingPeriod
Indicates that there is a defined time span or interval over which occurrences, quantities, or measurements related to an entity are counted or aggregated.
-
D.
invariantInterval
Indicates that a certain interval or range remains unchanged or constant under a specified transformation or set of conditions.
-
E.
supportsGuardIntervals
Indicates that one entity provides or is compatible with guard intervals used by another entity in a timing- or transmission-related context.
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd86f20f008190be7b5848af05f2b8 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd84561c7081909e5937c7816e492c |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd86f0cbfc8190b6665dd9b28d6345 |
completed | March 20, 2026, 5:42 p.m. |
Created at: March 20, 2026, 1:59 p.m.