Triple
T19686768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terpsichore |
E472730
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Clio |
—
|
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: Clio | Statement: [Terpsichore, sibling, Clio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clio Context triple: [Terpsichore, sibling, Clio]
-
A.
Clio
chosen
Clio is the Muse of history in Greek mythology, traditionally associated with the celebration and recording of heroic deeds.
-
B.
Minerva
Minerva is a supporting character in the 1997 Rodgers & Hammerstein television adaptation of Cinderella, appearing as one of the comedic stepsisters.
-
C.
Minerva
Minerva is the Roman goddess of wisdom, strategic warfare, and the arts, often identified with the Greek goddess Athena.
-
D.
Minerva
Minerva is an advanced, sentient computer (and later human embodiment) featured in Robert A. Heinlein’s science fiction works, notably as a key companion to Lazarus Long.
-
E.
Siris
Siris is a philosophical work by George Berkeley that explores metaphysics, theology, and the medicinal virtues of tar-water through a chain of reflective questions and arguments.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6420c3f50819082b64b1fa4335e56 |
completed | April 20, 2026, 3:11 p.m. |
Created at: April 10, 2026, 1:45 p.m.