Triple
T37134655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethan Lewis |
E919923
|
entity |
| Predicate | hasOnScreenRomanceWith |
P143936
|
FINISHED |
| Object | Kat Hernandez |
—
|
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: Kat Hernandez | Statement: [Ethan Lewis, hasOnScreenRomanceWith, Kat Hernandez]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenRomanceWith Context triple: [Ethan Lewis, hasOnScreenRomanceWith, Kat Hernandez]
-
A.
isRomanticLeadOf
Indicates that one entity serves as the primary romantic partner or love-interest counterpart to another entity within a narrative or story.
-
B.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
C.
hasRomanticEntanglementInPlot
Indicates that a romantic relationship or involvement between characters is a significant element within the narrative plot.
-
D.
hasRomanticPlotline
Indicates that there is a romantic storyline or relationship development present between the entities.
-
E.
romanticPartnerInSeries
chosen
Indicates that one character is portrayed as a romantic partner of another character within the context of a specific series or narrative.
- 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_69f76e9e9d008190a250b0387c992c74 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
Created at: May 3, 2026, 4:15 p.m.