Triple
T23515995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Witches (1990 film) |
E574367
|
entity |
| Predicate | featuresPracticalEffects |
P152692
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Witches (1990 film), featuresPracticalEffects, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresPracticalEffects Context triple: [The Witches (1990 film), featuresPracticalEffects, yes]
-
A.
featuresPractice
Indicates that something includes or offers a particular practice as a notable component or activity.
-
B.
featuresDemon
Indicates that an entity includes, depicts, or prominently involves a demon.
-
C.
featuresPowerUp
Indicates that one entity includes, provides, or incorporates a power-up as part of its content or functionality.
-
D.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
E.
featuresMode
Indicates that one entity operates in, supports, or is characterized by a particular mode or configuration specified by another entity.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa81ab4c8190b85c8f80754020ea |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:08 p.m.