Triple
T4525060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florentino Ariza |
E103356
|
entity |
| Predicate | loveType |
P26473
|
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: [Florentino Ariza, loveType, unrequited love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loveType Context triple: [Florentino Ariza, loveType, unrequited love]
-
A.
loveInterest
Indicates that one entity is the romantic object of affection or attraction for another entity.
-
B.
romanticArc
Indicates a developing or ongoing romantic relationship or storyline between the involved entities.
-
C.
hasRomanticTensionWith
chosen
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
D.
emotionallyAttachedTo
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another entity.
-
E.
isLoveSong
Indicates that a song’s primary theme or content centers on romantic love or affectionate emotional relationships.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd577490f48190ac1fb3cbf3d8a41e |
completed | March 20, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69bd521cf77c819083852de3094d1377 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:03 p.m.