Triple
T28098893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woldgate Woods |
E710173
|
entity |
| Predicate | hasSubjectRoleIn |
P192208
|
FINISHED |
| Object | David Hockney landscape paintings |
—
|
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: David Hockney landscape paintings | Statement: [Woldgate Woods, hasSubjectRoleIn, David Hockney landscape paintings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectRoleIn Context triple: [Woldgate Woods, hasSubjectRoleIn, David Hockney landscape paintings]
-
A.
hasSubjectPosition
Indicates that an entity occupies or is assigned to a particular subject role or position within a structure, context, or organization.
-
B.
hasHumanSubject
Indicates that an entity serves as the human participant or subject involved in an action, event, or relation.
-
C.
hasSubrole
Indicates that one role functions as a more specific, subordinate, or specialized version of another broader role.
-
D.
hasSemanticRole
Indicates that one entity functions as a specific semantic role (such as agent, patient, or instrument) in relation to another entity or event.
-
E.
hasSubjectPlace
Indicates that something is associated with or occurs in a particular subject-related place or location.
- 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_69ef9b70fd108190a875953b2e50ca91 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69fd026757a081909911a59a78652709 |
completed | May 7, 2026, 9:21 p.m. |
Created at: April 27, 2026, 9:03 p.m.