Triple
T25088105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werther |
E628378
|
entity |
| Predicate | loveRivalOf |
P115860
|
FINISHED |
| Object | Albert |
—
|
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: Albert | Statement: [Werther, loveRivalOf, Albert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loveRivalOf Context triple: [Werther, loveRivalOf, Albert]
-
A.
romanticRivalryWith
chosen
Indicates a mutual competitive relationship in which two entities vie for the romantic attention or affection of the same person.
-
B.
rivalOf
Indicates a relationship in which two entities compete against or oppose each other, often seeking advantage in the same domain or objective.
-
C.
rumoredLoverOf
Indicates that one entity is widely believed or speculated to be the romantic partner or lover of another entity, without confirmed evidence.
-
D.
protagonistLover
Indicates that one entity is the romantic partner or love interest of the story’s protagonist.
-
E.
fictionalRivalOf
Indicates a rivalry relationship that exists between two entities only within a fictional or narrative context.
- 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_69e2ff2f58e881908340527bc5d34f07 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f461e667a48190ad63646978cadf62 |
completed | May 1, 2026, 8:18 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:24 a.m.