Triple
T19178059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selene |
E469489
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Selene (Greek moon goddess) |
—
|
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: Selene (Greek moon goddess) | Statement: [Selene, namedAfter, Selene (Greek moon goddess)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Selene (Greek moon goddess) Context triple: [Selene, namedAfter, Selene (Greek moon goddess)]
-
A.
Selene
Selene is the tourist lunar excursion vehicle featured in Arthur C. Clarke’s science fiction novel "A Fall of Moondust."
-
B.
Selene
chosen
Selene is the Greek goddess and personification of the Moon, often depicted driving a silver chariot across the night sky.
-
C.
Luna
Luna is the gentle, talking moon character who serves as a wise, comforting friend and advisor to Bear in the children's television series "Bear in the Big Blue House."
-
D.
Luna
Luna is a municipality in the province of Apayao in the Cordillera Administrative Region of the Philippines, known for its rural landscapes and indigenous cultural heritage.
-
E.
Luna
Luna is the natural satellite of Earth, renowned for its phases, influence on tides, and prominence in human culture and mythology.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f619c60c81909d11489525add829 |
completed | April 20, 2026, 9:47 a.m. |
Created at: April 10, 2026, 12:07 p.m.