Triple
T31286194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Lover |
E797809
|
entity |
| Predicate | personaPortrayed |
P54972
|
FINISHED |
| Object | seductive lover |
—
|
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: seductive lover | Statement: [International Lover, personaPortrayed, seductive lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: personaPortrayed Context triple: [International Lover, personaPortrayed, seductive lover]
-
A.
characterPortrayedIs
chosen
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
B.
portrayedBy
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
C.
friendPortrayedBy
Indicates that a person’s friend is depicted or represented by a particular actor or performer.
-
D.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
-
E.
portrayalKnownFor
Indicates that a particular portrayal or role is the one for which an entity is especially recognized or famous.
- 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_69f224def9088190a37034eab3daf57f |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:13 p.m.