Triple
T30526838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Molly Cunningham |
E776870
|
entity |
| Predicate | hasRelationshipTypeWithJeremyFurlow |
P202490
|
FINISHED |
| Object | romantic interest |
—
|
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: romantic interest | Statement: [Molly Cunningham, hasRelationshipTypeWithJeremyFurlow, romantic interest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithJeremyFurlow Context triple: [Molly Cunningham, hasRelationshipTypeWithJeremyFurlow, romantic interest]
-
A.
hasRelationshipTypeWith Nobody Owens
Indicates that an entity stands in a specific, defined type of relationship to Nobody Owens.
-
B.
hasRelationshipTypeWith Frank Drebin
Indicates that there exists a specific type of relationship between an entity and Frank Drebin.
-
C.
hasRelationshipTypeWithJoelKnox
Indicates that an entity has a specific type of relationship or association with Joel Knox.
-
D.
hasRelationshipTypeWith Vince Tyler
Indicates that an entity is connected to Vince Tyler by a specific, characterized type of relationship.
-
E.
hasRelationshipTypeWithBenBoykewich
Indicates that an entity has a specific type of relationship or connection with Ben Boykewich.
- 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_69f2249c11508190ae7e955755ccfb01 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a008ac37dc081908d360574912f40ec |
completed | May 10, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_6a008a67d73881909855ab4cfca3c399 |
completed | May 10, 2026, 1:38 p.m. |
| PDg | Predicate description generation | batch_6a008ac2d0dc8190865ccedb2003d0ed |
completed | May 10, 2026, 1:40 p.m. |
Created at: April 29, 2026, 8:17 p.m.