Triple
T23624637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will Truman |
E583427
|
entity |
| Predicate | hasOnScreenRomanticInterest |
P93858
|
FINISHED |
| Object | Vince D'Angelo |
—
|
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: Vince D'Angelo | Statement: [Will Truman, hasOnScreenRomanticInterest, Vince D'Angelo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenRomanticInterest Context triple: [Will Truman, hasOnScreenRomanticInterest, Vince D'Angelo]
-
A.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
B.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
C.
hasOnScreenKissWith
Indicates that two entities share a romantic or affectionate kiss depicted visually within the same on-screen scene.
-
D.
romanticInvolvementUnderAlias
Indicates that two entities are romantically involved with each other while at least one of them is using an alias or false identity.
-
E.
hasLoveInterestInWork
chosen
Indicates that one entity is portrayed as a romantic love interest of another entity within a specific creative work.
- 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_69e248fc8d74819091bd5baef2f36f6f |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b17be6288190a409df700c1003bd |
completed | April 29, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:46 p.m.