Triple
T17537782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book VI of Nicomachean Ethics |
E427105
|
entity |
| Predicate | discusses |
P450
|
FINISHED |
| Object | sophia |
—
|
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: sophia | Statement: [Book VI of Nicomachean Ethics, discusses, sophia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: sophia Context triple: [Book VI of Nicomachean Ethics, discusses, sophia]
-
A.
Sophia
chosen
Sophia is a philosophical and theological concept signifying divine wisdom, often personified and associated with the rational principle of the cosmos.
-
B.
Sophia
Sophia is a small town located in Raleigh County in the southern part of West Virginia, United States.
-
C.
Sophia
Sophia was a prominent Byzantine empress of the Justinian dynasty, known for her political influence and role in imperial court affairs during the 6th century.
-
D.
Sophia
Sophia is a feminine given name of Greek origin meaning "wisdom," widely used across many cultures and languages.
-
E.
Sophia
Sophia is the birth name of American actress Sylvia Sidney, a prominent film and stage performer of the 1930s and later character roles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4536dbe908190ba7559f9561f05a2 |
completed | April 19, 2026, 4 a.m. |
Created at: April 10, 2026, 5:49 a.m.