Triple
T18967743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thor: Love and Thunder (2022) film score |
E464084
|
entity |
| Predicate | supportsSetting |
P89047
|
FINISHED |
| Object | cosmic locations |
—
|
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: cosmic locations | Statement: [Thor: Love and Thunder (2022) film score, supportsSetting, cosmic locations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsSetting Context triple: [Thor: Love and Thunder (2022) film score, supportsSetting, cosmic locations]
-
A.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
B.
supportsUse
Indicates that one entity enables, allows, or is compatible with the use or operation of another entity.
-
C.
supportsValue
Indicates that one entity provides justification, evidence, or backing for the truth, relevance, or appropriateness of a particular value associated with another entity.
-
D.
supportedIn
Indicates that one entity is valid, applicable, or functionally enabled within the context, environment, platform, or scope defined by another entity.
-
E.
coversSetting
chosen
Indicates that one entity includes or addresses a particular setting or context within its scope.
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6172888819090a8b3cb1db20496 |
completed | April 20, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, noon