Triple
T24046613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felicity Porter |
E595537
|
entity |
| Predicate | highSchoolCrush |
P152714
|
FINISHED |
| Object | Ben Covington |
—
|
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: Ben Covington | Statement: [Felicity Porter, highSchoolCrush, Ben Covington]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highSchoolCrush Context triple: [Felicity Porter, highSchoolCrush, Ben Covington]
-
A.
isChildhoodSweetheartOf
chosen
Indicates that two people were romantically involved with each other during their childhood or adolescence, typically as first or early sweethearts.
-
B.
formerHighSchool
Indicates that one entity previously attended or was enrolled at the other entity as their high school.
-
C.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
D.
exBoyfriendOf
Indicates that one person was formerly the romantic boyfriend of another person.
-
E.
rumoredLoverOf
Indicates that one entity is widely believed or speculated to be the romantic partner or lover of another entity, without confirmed evidence.
- 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_69e288c06a908190899cad4531f32c9a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9ca5a18819086da68b69eed8cc1 |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:16 p.m.