Triple
T4026389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Thin Red Line (1998 film) score |
E83599
|
entity |
| Predicate | supportsThemeOf |
P53515
|
FINISHED |
| Object | war and nature |
—
|
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: war and nature | Statement: [The Thin Red Line (1998 film) score, supportsThemeOf, war and nature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsThemeOf Context triple: [The Thin Red Line (1998 film) score, supportsThemeOf, war and nature]
-
A.
supportsProduct
Indicates that one entity provides assistance, compatibility, or necessary resources for the operation, use, or maintenance of a specified product.
-
B.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
C.
supportsUse
Indicates that one entity enables, allows, or is compatible with the use or operation of another entity.
-
D.
supportedAs
Indicates that one entity is accepted, recognized, or treated as being in the role, type, or representation of another entity.
-
E.
supportedIn
Indicates that one entity is valid, applicable, or functionally enabled within the context, environment, platform, or scope defined 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaed37e48190844032e7e77163e0 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fc78ec819092d4dab88d85a141 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa815f2c8190818c9ffd9d1bf478 |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:36 p.m.