Triple
T35812223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pearson family |
E1035260
|
entity |
| Predicate | portrayedAcross |
P199845
|
FINISHED |
| Object | multiple timelines |
—
|
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: multiple timelines | Statement: [Pearson family, portrayedAcross, multiple timelines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedAcross Context triple: [Pearson family, portrayedAcross, multiple timelines]
-
A.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
B.
portraysCharacterIn
Indicates that one entity depicts or represents a particular character within a work, such as a film, show, or other narrative medium.
-
C.
alsoPortrayedBy
Indicates that the same role or character is portrayed by an additional, different performer or actor.
-
D.
portrayedInCrossover
Indicates that an entity is depicted or appears as a character within a crossover work that combines elements from multiple distinct sources or franchises.
-
E.
isPortrayedIn
Indicates that an entity is depicted or represented within a particular work, medium, or portrayal.
- 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_69f76e1762408190b885a8456862e372 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
| PDg | Predicate description generation | batch_69ff5b224b8c8190bd0955876098ecc8 |
completed | May 9, 2026, 4:04 p.m. |
Created at: May 3, 2026, 4:06 p.m.