Triple
T23070765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginnie Moorehead |
E575186
|
entity |
| Predicate | hasLoveType |
P98395
|
FINISHED |
| Object | unrequited love |
—
|
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: unrequited love | Statement: [Ginnie Moorehead, hasLoveType, unrequited love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoveType Context triple: [Ginnie Moorehead, hasLoveType, unrequited love]
-
A.
hasLoveLifeCharacteristic
chosen
Indicates that an entity possesses a particular quality, status, or attribute related to its romantic or love life.
-
B.
loveInterestType
Indicates the specific kind or category of romantic or affectionate relationship that exists between the related entities.
-
C.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
D.
objectOfAffectionFor
Indicates that one entity is the target or recipient of another entity’s romantic or affectionate feelings.
-
E.
attitudeTowardLove
Indicates an entity’s feelings, beliefs, or stance regarding the concept or experience of love.
- 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_69e245bd6e4c8190bb8942245b68cad5 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18c5f17348190ab92cfdae9bcaeba |
completed | April 29, 2026, 4:43 a.m. |
| PD | Predicate disambiguation | batch_69ef89d5f71881908b9f9d0c8aab278c |
completed | April 27, 2026, 4:07 p.m. |
Created at: April 17, 2026, 3:56 p.m.