Triple
T9723368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evelyn Abbott |
E235536
|
entity |
| Predicate | portrayedByInUniverse |
P1507
|
FINISHED |
| Object | Emily Blunt in A Quiet Place |
—
|
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: Emily Blunt in A Quiet Place | Statement: [Evelyn Abbott, portrayedByInUniverse, Emily Blunt in A Quiet Place]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedByInUniverse Context triple: [Evelyn Abbott, portrayedByInUniverse, Emily Blunt in A Quiet Place]
-
A.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
B.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
C.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
-
D.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
E.
portraysFictionalEntity
Indicates that one entity depicts, represents, or plays the role of a fictional character or figure.
- 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e75abd48190a6e6679ec51496e8 |
completed | April 1, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69cd03c6ffc88190a5e9569e19122ad5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:20 p.m.