Triple
T16684372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erica Kane |
E405419
|
entity |
| Predicate | portrayalDurationYears |
P124245
|
FINISHED |
| Object | over 40 years |
—
|
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: over 40 years | Statement: [Erica Kane, portrayalDurationYears, over 40 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalDurationYears Context triple: [Erica Kane, portrayalDurationYears, over 40 years]
-
A.
portrayalEndYear
Indicates the year in which a particular portrayal of an entity (such as a role, character, or representation) concluded.
-
B.
portraysFromAge
Indicates that one entity depicts another entity starting from a specified age of the depicted entity.
-
C.
notablePortrayalPeriod
Indicates the time period during which a particular portrayal or depiction of something or someone is especially recognized or notable.
-
D.
portrayalContinuity
Indicates that the same character is portrayed consistently across different works, installments, or versions, maintaining continuity in their depiction.
-
E.
activeYearsInFilm
Indicates the span of years during which an entity was actively involved in film-related work or roles.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d71a66881908c8d06cc074fdf29 |
completed | April 18, 2026, 12:47 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:19 a.m.