Triple
T33675107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amanda McCready |
E862736
|
entity |
| Predicate | ethnicityInFilm |
P178064
|
FINISHED |
| Object | white American |
—
|
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: white American | Statement: [Amanda McCready, ethnicityInFilm, white American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethnicityInFilm Context triple: [Amanda McCready, ethnicityInFilm, white American]
-
A.
leadActorEthnicity
Indicates the ethnic background or identity of the primary (lead) actor in a work.
-
B.
ethnicityInSeries
Indicates that a character’s ethnicity as portrayed or identified within a specific series is being specified.
-
C.
featuresInterracialCasting
Indicates that the work includes casting choices where performers of different racial backgrounds appear together in significant roles or interactions.
-
D.
hasEthnicityInFiction
chosen
Indicates that a fictional character or entity is portrayed as having a particular ethnicity within a narrative or fictional context.
-
E.
portrayedByEthnicity
Indicates that an entity is portrayed or represented by someone of a specified ethnic background.
- 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_69f34985885c8190914322f492e04703 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 1, 2026, 1:43 a.m.