Triple
T28666180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butch Bowers |
E725591
|
entity |
| Predicate | relationshipToHenryBowers |
P87836
|
FINISHED |
| Object | father |
—
|
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: father | Statement: [Butch Bowers, relationshipToHenryBowers, father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToHenryBowers Context triple: [Butch Bowers, relationshipToHenryBowers, father]
-
A.
relationshipToHenry
chosen
Indicates the specific type of relationship or connection that an entity has to Henry.
-
B.
relationshipTypeWithHenryWilcox
Indicates the specific nature or category of relationship that an entity has with Henry Wilcox.
-
C.
relationshipToJoeCinque
Indicates a specified type of relationship or connection that an entity has to Joe Cinque.
-
D.
relationshipTypeWithHudBannon
Indicates the specific nature or category of relationship that an entity has with the person or entity named Hud Bannon.
-
E.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
- F. None of above.
Provenance (3 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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_6a00474f08908190bc8ae3b320ec887b |
completed | May 10, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_6a0045dc3bd48190a9e0520f3ef3f067 |
completed | May 10, 2026, 8:46 a.m. |
Created at: April 28, 2026, 5:01 a.m.