Triple
T29845130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horace Albert McKinney |
E757908
|
entity |
| Predicate | givenFirstAndMiddleNamesOf |
P167660
|
FINISHED |
| Object | "Bones" McKinney |
—
|
NE NERFINISHED |
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: "Bones" McKinney | Statement: [Horace Albert McKinney, givenFirstAndMiddleNamesOf, "Bones" McKinney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: givenFirstAndMiddleNamesOf Context triple: [Horace Albert McKinney, givenFirstAndMiddleNamesOf, "Bones" McKinney]
-
A.
givenName
Indicates the personal first name assigned to an individual.
-
B.
fullGivenNameOf
Indicates that one entity is the complete, formal given name corresponding to another entity (such as a person or identifier).
-
C.
givenNameFor
Indicates that one entity is the personal first name assigned to or used for another entity.
-
D.
givenNameBy
Indicates that one entity has been assigned or provided a specific given (first) name by another entity.
-
E.
givenNameIn
Indicates that an entity has a specific first or given name in a particular language or naming context.
- 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_69f224593f6c81908785a560fe659f58 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6760cbbcc81908cb6522f8eb38000 |
completed | May 2, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66bd123108190b451eb6e23842adb |
completed | May 2, 2026, 9:25 p.m. |
Created at: April 29, 2026, 5:41 p.m.