Triple
T19935389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alma Brown |
E479161
|
entity |
| Predicate | relationshipTypeWithHudBannon |
P137899
|
FINISHED |
| Object | complex emotional tension |
—
|
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: complex emotional tension | Statement: [Alma Brown, relationshipTypeWithHudBannon, complex emotional tension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithHudBannon Context triple: [Alma Brown, relationshipTypeWithHudBannon, complex emotional tension]
-
A.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
B.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
-
C.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
E.
relationshipToTheDude
Indicates the specific type of personal or social relationship that one entity has to the individual referred to as "the Dude."
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a161a6c819084165ea528ec2f64 |
completed | April 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:53 p.m.