Triple
T16779441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oscar Isaac as Nathan Bateman |
E407817
|
entity |
| Predicate | usesSubstanceInFiction |
P120354
|
FINISHED |
| Object | alcohol |
—
|
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: alcohol | Statement: [Oscar Isaac as Nathan Bateman, usesSubstanceInFiction, alcohol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSubstanceInFiction Context triple: [Oscar Isaac as Nathan Bateman, usesSubstanceInFiction, alcohol]
-
A.
hasFictionalSubstance
Indicates that one entity includes, contains, or involves a fictional or imaginary substance as part of its composition, setting, or narrative.
-
B.
substancePersonified
Indicates that an abstract substance or concept is represented or treated as if it were a person or sentient being.
-
C.
usedSubstance
Indicates that an entity has consumed, applied, or otherwise made use of a particular substance.
-
D.
materialUsedInFiction
chosen
Indicates that a particular material (such as a substance or resource) is used, featured, or plays a role within a fictional work or narrative.
-
E.
hasSubstance
Indicates that one entity contains, consists of, or is composed of a particular substance or material.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b21401b881909bbbc7382e851a90 |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.