Triple
T6100980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Farley |
E135992
|
entity |
| Predicate | hasWritingSubject |
P18026
|
FINISHED |
| Object | horses |
—
|
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: horses | Statement: [Walter Farley, hasWritingSubject, horses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWritingSubject Context triple: [Walter Farley, hasWritingSubject, horses]
-
A.
hasWrittenFor
Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
-
B.
hasWrittenAbout
Indicates that one entity has authored content or material discussing, analyzing, or referencing another entity.
-
C.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
D.
hasWorkSubject
chosen
Indicates that a work (such as a document, artwork, or project) is about or concerns a particular subject or topic.
-
E.
hasWrittenForm
Indicates that an entity is associated with a specific written or textual representation.
- 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_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3aa9908190865be98ada141d37 |
completed | March 22, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c049f5ac988190b62ba565153aaa35 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.