Triple
T15905513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crossroads Films |
E385701
|
entity |
| Predicate | createsContentFor |
P120998
|
FINISHED |
| Object | cinema |
—
|
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: cinema | Statement: [Crossroads Films, createsContentFor, cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: createsContentFor Context triple: [Crossroads Films, createsContentFor, cinema]
-
A.
publishesContent
Indicates that one entity makes content created by another entity publicly available or distributed through some medium.
-
B.
creationType
Indicates the manner or process by which something was brought into existence or produced.
-
C.
curatesContentFrom
Indicates that one entity selects, organizes, and presents content that originates from another entity.
-
D.
collectsContent
Indicates that one entity gathers, acquires, or accumulates content from another entity or source.
-
E.
GCContent
Indicates the proportion of guanine (G) and cytosine (C) bases relative to the total nucleotide content in a DNA or RNA sequence.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:52 a.m.