Triple
T28786886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucy Warriner |
E726837
|
entity |
| Predicate | relationshipTypeWith Jerry Warriner |
P202385
|
FINISHED |
| Object | tumultuous marriage |
—
|
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: tumultuous marriage | Statement: [Lucy Warriner, relationshipTypeWith Jerry Warriner, tumultuous marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Jerry Warriner Context triple: [Lucy Warriner, relationshipTypeWith Jerry Warriner, tumultuous marriage]
-
A.
relationshipToJerryLundegaard
Indicates the specific familial, social, or professional relationship that one entity has to Jerry Lundegaard.
-
B.
relationshipTypeWithJerryPayne
Indicates the specific nature or category of relationship that an entity has with Jerry Payne.
-
C.
relationshipToJerryConlaine
Indicates the specific type of relationship or connection an entity has to Jerry Conlaine.
-
D.
relationshipToAmyJuergens
Indicates the specific interpersonal or familial connection that an entity has to Amy Juergens.
-
E.
relationshipTypeWith Larry Darrell
Indicates the specific type or nature of the relationship that an entity has with Larry Darrell.
- 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_69f0319aabec81908368720196f69a35 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_6a007899cadc8190a04edd503eaf6514 |
completed | May 10, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_6a0078493e088190b0c5047cbe75d304 |
completed | May 10, 2026, 12:21 p.m. |
| PDg | Predicate description generation | batch_6a00789927708190b031d3a9d5f4f68e |
completed | May 10, 2026, 12:22 p.m. |
Created at: April 28, 2026, 6:21 a.m.