Triple
T28274983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joanna Stayton |
E712961
|
entity |
| Predicate | relationshipWithDeanProffitt |
P201342
|
FINISHED |
| Object | initially antagonistic |
—
|
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: initially antagonistic | Statement: [Joanna Stayton, relationshipWithDeanProffitt, initially antagonistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithDeanProffitt Context triple: [Joanna Stayton, relationshipWithDeanProffitt, initially antagonistic]
-
A.
relationshipToBoDecker
Indicates the specific type of personal or social relationship an entity has with Bo Decker.
-
B.
relationshipWithDelGriffith
Indicates that one entity has some form of personal or social relationship with the individual referred to as Del Griffith.
-
C.
relationshipToSamSpade
Indicates that one entity has a specified personal or social relationship to the individual Sam Spade.
-
D.
relationshipTypeWithDeborahOwens
Indicates the specific nature or category of relationship an entity has with Deborah Owens.
-
E.
relationshipTypeWithJeffSadecki
Indicates the specific nature or category of relationship that an entity has with Jeff Sadecki.
- 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_69efb52275788190ae5181ccebef18ce |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ffecdcbac4819093b725a7dbe0e61b |
completed | May 10, 2026, 2:26 a.m. |
| PD | Predicate disambiguation | batch_69ffec3633288190adbbd84e277708dc |
completed | May 10, 2026, 2:23 a.m. |
| PDg | Predicate description generation | batch_69ffecdbe62081909f901e7d4db69d60 |
completed | May 10, 2026, 2:26 a.m. |
Created at: April 27, 2026, 11:19 p.m.