Triple
T10251796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philosophy, Politics and Economics |
E240360
|
entity |
| Predicate | coreTopicsInclude |
P43765
|
FINISHED |
| Object | ethics |
—
|
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: ethics | Statement: [Philosophy, Politics and Economics, coreTopicsInclude, ethics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreTopicsInclude Context triple: [Philosophy, Politics and Economics, coreTopicsInclude, ethics]
-
A.
coreCategory
Indicates that one entity is the primary or fundamental category to which another entity belongs or is classified under.
-
B.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
C.
typicalCourseTopic
chosen
Indicates that a given topic is commonly or characteristically covered as part of a particular course.
-
D.
includesTopics
Indicates that one entity contains, covers, or addresses the specified topics as part of its content or scope.
-
E.
featuresTopic
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d328272c8190a3548d7f7f38cfc4 |
completed | April 7, 2026, 9:49 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ebd6c88190a1f3f4a72a99d6fe |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:29 a.m.