Triple
T28167629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sleep (1963 film) |
E715370
|
entity |
| Predicate | firstScreeningPlace |
P33023
|
FINISHED |
| Object | Cinema Theatre, New York City |
—
|
NE NERFINISHED |
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: Cinema Theatre, New York City | Statement: [Sleep (1963 film), firstScreeningPlace, Cinema Theatre, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstScreeningPlace Context triple: [Sleep (1963 film), firstScreeningPlace, Cinema Theatre, New York City]
-
A.
firstScreeningLocation
chosen
Indicates the location where something (such as a person, item, or case) is initially screened or evaluated for the first time.
-
B.
firstScreeningEvent
Indicates the event representing the earliest or initial screening occurrence associated with an entity.
-
C.
firstScreenedAs
Indicates that an entity was initially shown, presented, or tested in a particular screening context or medium.
-
D.
firstScreeningDate
Indicates the date on which something (such as a film, show, or individual) is first formally screened or evaluated.
-
E.
screeningVenue
Indicates the place or location where a screening (such as a film or event showing) 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_69efd6b340f0819095680e15dcdc1830 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69ffc083a54c8190ac80d05ee8d20a6b |
completed | May 9, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69ffbfeb05b88190b4d50ce8124004d9 |
completed | May 9, 2026, 11:14 p.m. |
Created at: April 27, 2026, 10:10 p.m.