Triple
T11760906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaserDisc |
E279651
|
entity |
| Predicate | CLVFeature |
P52407
|
FINISHED |
| Object | longer playing time |
—
|
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: longer playing time | Statement: [LaserDisc, CLVFeature, longer playing time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CLVFeature Context triple: [LaserDisc, CLVFeature, longer playing time]
-
A.
recognizedFeature
Indicates that a particular feature has been identified and acknowledged as present or valid in relation to an entity or context.
-
B.
compositionalFeature
chosen
Indicates that one entity is a structural or constituent feature that forms part of the composition or makeup of another entity.
-
C.
targetFeature
Indicates that one entity is the specific feature, attribute, or characteristic that another entity is directed toward, focused on, or intended to affect.
-
D.
continuityFeature
Indicates that one entity serves as a continuity-related element (such as a transition, connector, or linking feature) that maintains or supports an ongoing, coherent relationship between two points, states, or segments.
-
E.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a52386708190b744746a2db37495 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.