Triple
T614918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Independent Spirit Award for Best Cinematography |
E12181
|
entity |
| Predicate | typicalCeremonyTime |
P6833
|
FINISHED |
| Object | late February |
—
|
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: late February | Statement: [Independent Spirit Award for Best Cinematography, typicalCeremonyTime, late February]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCeremonyTime Context triple: [Independent Spirit Award for Best Cinematography, typicalCeremonyTime, late February]
-
A.
ceremonyTiming
Indicates the temporal relationship specifying when a ceremony occurs or is scheduled to occur.
-
B.
typicalTimes
chosen
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
C.
ceremonyType
Indicates the specific kind or category of ceremony associated with an event or relationship.
-
D.
ceremonyHeldOn
Indicates that a specific ceremony took place on a particular date or day.
-
E.
ceremonyLocation
Indicates the place where a ceremony is held or takes place.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e0a0f588190b953fdb585263307 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfbcbf88190a854921dc531eba8 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.