Triple
T28638716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harsh Times |
E724860
|
entity |
| Predicate | characterPlayedBy_Eva Longoria |
P1507
|
FINISHED |
| Object | Sylvia |
—
|
NE NERFINISHED |
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: Sylvia | Statement: [Harsh Times, characterPlayedBy_Eva Longoria, Sylvia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedBy_Eva Longoria Context triple: [Harsh Times, characterPlayedBy_Eva Longoria, Sylvia]
-
A.
leadActressCharacterName
Indicates the name of the character portrayed by the lead actress in a given work.
-
B.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
C.
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.
-
D.
characterPlayedBy_MichelleRyan
Indicates that the subject is a character portrayed or played by Michelle Ryan.
-
E.
leadActressPlaysCharacter
Indicates that a lead actress portrays or performs the role of a specific character.
- 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_69f01d8328c48190bc0e5f9b9b848582 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: April 28, 2026, 4:42 a.m.