Triple
T20881215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Oakes |
E514152
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Cast of Thousands |
—
|
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: Cast of Thousands | Statement: [Philip Oakes, notableWork, Cast of Thousands]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cast of Thousands Context triple: [Philip Oakes, notableWork, Cast of Thousands]
-
A.
Cast of Thousands
chosen
Cast of Thousands is the second studio album by English alternative rock band Elbow, noted for its expansive, atmospheric sound and emotional songwriting.
-
B.
The Co-Stars
The Co-Stars are a music production duo known for crafting polished, radio-ready hip hop and R&B tracks.
-
C.
The Throngs
The Throngs is an alternative English title for the film or work commonly known as The Crowds.
-
D.
The Crowds
The Crowds is an English title for the 39th chapter of the Qur’an, which emphasizes sincere worship of God alone and contrasts the fates of believers and disbelievers.
-
E.
In a Crowd of Thousands
"In a Crowd of Thousands" is a musical number from the stage adaptation of the animated film Anastasia, in which characters recall a pivotal encounter during a royal parade.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c67974348190bd3484032c0d7b31 |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 12:46 p.m.