Triple
T19885471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barton Keyes |
E477886
|
entity |
| Predicate | relationshipToWalterNeff |
P137705
|
FINISHED |
| Object | Boss |
—
|
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: Boss | Statement: [Barton Keyes, relationshipToWalterNeff, Boss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToWalterNeff Context triple: [Barton Keyes, relationshipToWalterNeff, Boss]
-
A.
relationshipToWalterBurns
Indicates the specific nature of the relationship an entity has with Walter Burns, such as familial, professional, or social connection.
-
B.
relationshipToElaineBenes
Indicates a person's specific relational connection (such as friend, partner, or family member) to Elaine Benes.
-
C.
relationshipToWalterSobchak
Indicates the specific personal or social relationship that one entity has to Walter Sobchak.
-
D.
relationshipTypeWithDanielPlainview
Indicates the specific nature or category of relationship that an entity has with Daniel Plainview.
-
E.
relationshipWithDanielPlainview
Indicates a relationship or connection that an entity has with Daniel Plainview, such as familial, professional, or social ties.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659093df081909d3be9c3caeb79ba |
completed | April 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
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, 1:52 p.m.