Triple
T7645072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plane Crazy |
E173098
|
entity |
| Predicate | firstPublicScreeningType |
P9177
|
FINISHED |
| Object | test screening |
—
|
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: test screening | Statement: [Plane Crazy, firstPublicScreeningType, test screening]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPublicScreeningType Context triple: [Plane Crazy, firstPublicScreeningType, test screening]
-
A.
screeningType
chosen
Indicates the specific method or category of screening applied in a screening process or evaluation.
-
B.
firstScreeningEvent
Indicates the event representing the earliest or initial screening occurrence associated with an entity.
-
C.
firstAppearanceType
Indicates the type or category of context (e.g., medium, format, or work) in which an entity makes its first recorded appearance.
-
D.
introducedInTheater
Indicates that something (such as a film, play, or performance) was first presented or made available to the public in a theater setting.
-
E.
firstScreeningLocation
Indicates the location where something (such as a person, item, or case) is initially screened or evaluated for the first time.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faf2aa1c8190945a691e46300ef2 |
completed | March 27, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e9ef1c81909c8bff716541ac1f |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:58 p.m.