Triple
T25195248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denny Duquette |
E630981
|
entity |
| Predicate | relationshipTypeWithIzzieStevens |
P179989
|
FINISHED |
| Object | fiancé |
—
|
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: fiancé | Statement: [Denny Duquette, relationshipTypeWithIzzieStevens, fiancé]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithIzzieStevens Context triple: [Denny Duquette, relationshipTypeWithIzzieStevens, fiancé]
-
A.
relationshipTypeWithRoryGilmore
Indicates the specific nature or category of relationship that an entity has with Rory Gilmore.
-
B.
relationshipTypeWithLorelai
Indicates the specific nature or category of relationship that an entity has with Lorelai.
-
C.
relationshipToJaneRizzoli
Indicates the specific familial, social, or professional relationship that one entity has to Jane Rizzoli.
-
D.
hasRelationshipTypeWithRoryGilmore
Indicates that an entity has a specific type of interpersonal relationship or connection with Rory Gilmore.
-
E.
relationshipTypeWithStephanie Ramzinski
Indicates the specific nature or category of relationship that an entity has with Stephanie Ramzinski.
- 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 21, 2026, 12:46 p.m.