Triple
T25134284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William (Westworld) |
E629611
|
entity |
| Predicate | portrayalAge |
P161441
|
FINISHED |
| Object | older William portrayed by Ed Harris |
—
|
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: older William portrayed by Ed Harris | Statement: [William (Westworld), portrayalAge, older William portrayed by Ed Harris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalAge Context triple: [William (Westworld), portrayalAge, older William portrayed by Ed Harris]
-
A.
portraysFromAge
Indicates that one entity depicts another entity starting from a specified age of the depicted entity.
-
B.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
C.
portrayedByCharacterAgeApprox
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
-
D.
portrayedAsAdultBy
Indicates that one entity is depicted or represented as an adult by another entity (such as an artist, author, or creator).
-
E.
portrayalDurationYears
Indicates the number of years an entity has continuously portrayed or represented another entity or role.
- 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f613bc641c819084343cc78d080640 |
completed | May 2, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f613502d808190b89927e5e734b43a |
completed | May 2, 2026, 3:08 p.m. |
Created at: April 18, 2026, 6:28 a.m.