Triple
T10974519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benedick |
E259332
|
entity |
| Predicate | relationshipTypeWithBeatrice |
P38921
|
FINISHED |
| Object | enemies to lovers |
—
|
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: enemies to lovers | Statement: [Benedick, relationshipTypeWithBeatrice, enemies to lovers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithBeatrice Context triple: [Benedick, relationshipTypeWithBeatrice, enemies to lovers]
-
A.
relationshipTypeWithBertieWooster
Indicates the specific nature or category of relationship an entity has with Bertie Wooster.
-
B.
relationshipToOdette
Indicates the specific familial, social, or interpersonal connection that an entity has with Odette.
-
C.
relationshipToIsabelArcher
Indicates the specific personal or social connection that an entity has to Isabel Archer.
-
D.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
E.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f3794c8190b1992b4695139b62 |
completed | April 9, 2026, 9:31 a.m. |
| PD | Predicate disambiguation | batch_69d72e8c27cc81908050590b7a04cafd |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:24 p.m.