Triple
T21250701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naomie Harris |
E523734
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Moonlight |
—
|
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: Moonlight | Statement: [Naomie Harris, notableWork, Moonlight]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moonlight Context triple: [Naomie Harris, notableWork, Moonlight]
-
A.
Moonlight
"Moonlight" is a country song by the American duo Love and Theft, known for its smooth harmonies and romantic, laid-back vibe.
-
B.
Moonlight
"Moonlight" is a popular emo-rap song by American rapper XXXTentacion, known for its melodic style and posthumous chart success.
-
C.
Moonlight
Moonlight is an anime television series produced by Pastel Productions.
-
D.
Moonlight
"Moonlight" is a renowned late-19th-century landscape painting by American artist Ralph Albert Blakelock, celebrated for its moody, atmospheric depiction of a moonlit scene.
-
E.
Moonlight
chosen
Moonlight is a critically acclaimed 2016 coming-of-age drama film that explores themes of identity, sexuality, and race through the life of a young Black man growing up in Miami.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359da6e08190a96c471463c2388d |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 3:56 p.m.