Triple
T17844050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa Miller Hughes |
E445608
|
entity |
| Predicate | portrayalDuration |
P124245
|
FINISHED |
| Object | several decades |
—
|
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: several decades | Statement: [Lisa Miller Hughes, portrayalDuration, several decades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalDuration Context triple: [Lisa Miller Hughes, portrayalDuration, several decades]
-
A.
portrayalDurationYears
chosen
Indicates the number of years an entity has continuously portrayed or represented another entity or role.
-
B.
portrayalContinuity
Indicates that the same character is portrayed consistently across different works, installments, or versions, maintaining continuity in their depiction.
-
C.
portrayalStart
Indicates the point in time or sequence at which a particular portrayal or depiction of something begins.
-
D.
portrayalEndYear
Indicates the year in which a particular portrayal of an entity (such as a role, character, or representation) concluded.
-
E.
portrayalFormat
Indicates the medium or format in which something is portrayed or represented (e.g., painting, sculpture, film, digital).
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ff980048190b496c55b83b3b318 |
completed | April 19, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e266888190ae976b4b7d5b886f |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:16 a.m.