Triple
T109391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SnagFilms |
E2210
|
entity |
| Predicate | contentLicensingModel |
P181
|
FINISHED |
| Object | licensed films |
—
|
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: licensed films | Statement: [SnagFilms, contentLicensingModel, licensed films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contentLicensingModel Context triple: [SnagFilms, contentLicensingModel, licensed films]
-
A.
licenseFamily
Indicates that one license belongs to, is derived from, or is categorized under a broader family or class of related licenses.
-
B.
license
chosen
Indicates that one entity has granted another entity formal permission or authorization to use, perform, or exploit something under specified terms.
-
C.
publishingModel
Indicates the method or framework by which content is produced, distributed, and made publicly available.
-
D.
hasLegalDepositRightFor
Indicates that an entity holds the legal right to receive, collect, or claim deposited materials (such as publications or documents) from another entity under legal deposit regulations.
-
E.
fundingModel
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563fd2fc819090265edbfe3092d6 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.