Triple
T10182841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashley Moody |
E236829
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Moody |
E115868
|
NE FINISHED |
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: Moody | Statement: [Ashley Moody, familyName, Moody]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moody Context triple: [Ashley Moody, familyName, Moody]
-
A.
Moody
chosen
Moody is a surname of English origin most famously associated with the 19th-century American evangelist Dwight L. Moody.
-
B.
The Mood
"The Mood" is a track by Kid Cudi from his album *Man on the Moon II: The Legend of Mr. Rager*, known for its introspective lyrics and atmospheric production.
-
C.
Mood
"Mood" is a song by Canadian singer-songwriter Jessie Reyez that showcases her raw, emotionally charged style and confessional lyricism.
-
D.
Mood
Mood is an American hip hop group known for its underground, jazz-influenced sound and collaborations with producer Hi-Tek.
-
E.
Mood
"Mood" is a popular Afrobeats song by Nigerian artist Wizkid, known for its smooth, laid-back vibe and melodic delivery.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded3408b88190a7d981a6dcea48d9 |
completed | April 2, 2026, 4:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3179b9de88190ba3beb7d6dbf7ad3 |
completed | April 6, 2026, 2:16 a.m. |
Created at: March 30, 2026, 9:12 p.m.