Triple
T21842400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Castellano |
E539285
|
entity |
| Predicate | hasRomanticMoment |
P98484
|
FINISHED |
| Object | confession of love on an airplane to Mindy Lahiri |
—
|
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: confession of love on an airplane to Mindy Lahiri | Statement: [Danny Castellano, hasRomanticMoment, confession of love on an airplane to Mindy Lahiri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRomanticMoment Context triple: [Danny Castellano, hasRomanticMoment, confession of love on an airplane to Mindy Lahiri]
-
A.
hasRomanticMisadventures
Indicates that an entity experiences a series of problematic, comical, or unsuccessful romantic relationships or encounters.
-
B.
hasRomanticSceneAt
chosen
Indicates that a romantic scene occurs at a specific location or point in time within a work or context.
-
C.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
D.
hasOnScreenKissWith
Indicates that two entities share a romantic or affectionate kiss depicted visually within the same on-screen scene.
-
E.
romanticOutcome
Indicates that a romantic relationship or interaction between entities results in a particular outcome, such as success, failure, or change in status.
- 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_69e0c476c3c88190a92d08ebb59a128a |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7ad76d48190a1905cfdbe866323 |
completed | April 28, 2026, 12:27 p.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:55 p.m.