Triple
T16779431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oscar Isaac as Nathan Bateman |
E407817
|
entity |
| Predicate | conductsInFiction |
P124603
|
FINISHED |
| Object | Turing test-like experiment |
—
|
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: Turing test-like experiment | Statement: [Oscar Isaac as Nathan Bateman, conductsInFiction, Turing test-like experiment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conductsInFiction Context triple: [Oscar Isaac as Nathan Bateman, conductsInFiction, Turing test-like experiment]
-
A.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
B.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
-
C.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
D.
fictionalContent
Indicates that one entity is content whose subject matter, events, or characters are imaginary or invented rather than factual.
-
E.
flowsThroughInFiction
Indicates that, within a fictional context or narrative, one entity (typically a river or similar medium) passes through, traverses, or courses across another entity (such as a location or region).
- 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_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. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.