Triple
T26255644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Domestic Violence Hotline |
E656705
|
entity |
| Predicate | loveisrespectFocus |
P160170
|
FINISHED |
| Object | teen and young adult dating abuse |
—
|
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: teen and young adult dating abuse | Statement: [National Domestic Violence Hotline, loveisrespectFocus, teen and young adult dating abuse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loveisrespectFocus Context triple: [National Domestic Violence Hotline, loveisrespectFocus, teen and young adult dating abuse]
-
A.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
B.
loveInterest
Indicates that one entity is the romantic object of affection or attraction for another entity.
-
C.
viewOnLove
Indicates a person’s attitude, belief, or perspective regarding the concept or experience of love.
-
D.
relationshipFocus
Indicates a relationship where particular attention, priority, or emphasis is placed on the connection between two or more entities.
-
E.
emotionalFocusOf
Indicates that one entity is the primary target or center of another entity’s emotions or emotional attention.
- F. None of above. chosen
Provenance (4 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60dfaeebc8190ac01d3a0030acf55 |
completed | May 2, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69f5f7ff548c8190a23e98c5e66e0bc7 |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f5ffc6268c8190b63f6360ebadab73 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 26, 2026, 9:08 p.m.