Triple
T21721614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evan Buckley |
E536169
|
entity |
| Predicate | hasRomanticStorylines |
P19974
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Evan Buckley, hasRomanticStorylines, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRomanticStorylines Context triple: [Evan Buckley, hasRomanticStorylines, yes]
-
A.
hasRomanticMisadventures
Indicates that an entity experiences a series of problematic, comical, or unsuccessful romantic relationships or encounters.
-
B.
hasRomanticSceneAt
Indicates that a romantic scene occurs at a specific location or point in time within a work or context.
-
C.
canRomanceMultipleCharacters
Indicates that an entity is able to pursue romantic relationships with more than one character.
-
D.
hasMarriagePlot
chosen
Indicates that the work’s narrative centrally involves courtship, romantic relationships, or the progression toward marriage as a key plot element.
-
E.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
- 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efd96f1fbc8190a202f834aec1a319 |
completed | April 27, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:47 p.m.