Triple
T31446143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Naveen |
E802190
|
entity |
| Predicate | romanticSceneLocation |
P20834
|
FINISHED |
| Object | bayou |
—
|
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: bayou | Statement: [Prince Naveen, romanticSceneLocation, bayou]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticSceneLocation Context triple: [Prince Naveen, romanticSceneLocation, bayou]
-
A.
romanticSceneWith
Indicates a scene or situation in which the two entities are engaged together in a romantic context or interaction.
-
B.
placeOfSetting
chosen
Indicates the location or environment where an event, scene, or situation takes place.
-
C.
romanticLeadIn
Indicates that one entity is the primary romantic interest or central romantic partner of another within a narrative or context.
-
D.
romanticPattern
Indicates a recurring style, tendency, or structure in how romantic relationships or attractions develop or are expressed between entities.
-
E.
romanticPlotFunction
Indicates a narrative relationship where characters are involved in or contribute to a romantic storyline or romantic development within the plot.
- 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_69f348c5a6bc819092a557e95438976f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 30, 2026, 9:09 p.m.