Triple
T32465975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aquinas: Moral, Political, and Legal Theory |
E829704
|
entity |
| Predicate | defendsViewOf |
P40990
|
FINISHED |
| Object | Thomas Aquinas |
—
|
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: Thomas Aquinas | Statement: [Aquinas: Moral, Political, and Legal Theory, defendsViewOf, Thomas Aquinas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defendsViewOf Context triple: [Aquinas: Moral, Political, and Legal Theory, defendsViewOf, Thomas Aquinas]
-
A.
protectsViewOf
Indicates that one entity blocks or shields the view or visibility of another entity.
-
B.
defends
Indicates that one entity protects or supports another entity against attack, criticism, or harm.
-
C.
defendedAs
Indicates that one entity is presented, argued, or justified as being equivalent to or serving the role of another entity in a defensive or protective context.
-
D.
defendsPosition
Indicates that one entity actively supports and justifies a stance, claim, or viewpoint in response to challenge or opposition.
-
E.
defendsConcept
chosen
Indicates that one entity actively supports and argues in favor of a particular concept, idea, or theory, often in response to criticism or challenge.
- 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_69f3491ee87c81908cbf5890079c2af6 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: May 1, 2026, 12:57 a.m.