Triple
T32252349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milburn Drysdale |
E823915
|
entity |
| Predicate | relationshipToClampetts |
P206236
|
FINISHED |
| Object | banker |
—
|
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: banker | Statement: [Milburn Drysdale, relationshipToClampetts, banker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToClampetts Context triple: [Milburn Drysdale, relationshipToClampetts, banker]
-
A.
relationshipToPawneeNation
Indicates the specific type of familial, legal, historical, or political relationship that an entity has with the Pawnee Nation.
-
B.
relationshipToKittyBennet
Indicates the specific type of personal or familial connection an entity has to Kitty Bennet.
-
C.
relationshipToBelcherChildren
Indicates the specific familial or caretaking relationship an entity has to the Belcher children.
-
D.
relationshipToMegMurry
Indicates the specific type of relationship or connection an entity has to Meg Murry.
-
E.
relationshipToMickey
Indicates the specific familial, social, or other personal connection that one entity has to Mickey.
- 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_69f3490db0748190bfef6e50c95d39d3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 12:41 a.m.