Triple
T15328864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Allegory |
E366480
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | Conway the Machine |
E395860
|
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: Conway the Machine | Statement: [The Allegory, featuresArtist, Conway the Machine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Conway the Machine Context triple: [The Allegory, featuresArtist, Conway the Machine]
-
A.
Conway the Machine
chosen
Conway the Machine is an American rapper from Buffalo, New York, known for his gritty lyricism, street-oriented narratives, and work as a core member of the Griselda collective.
-
B.
Yungblud
Yungblud is an English singer, songwriter, and musician known for his energetic blend of pop-punk, alternative rock, and socially charged lyrics.
-
C.
Brent Faiyaz
Brent Faiyaz is an American singer, songwriter, and producer known for his atmospheric R&B sound and introspective, emotionally raw lyrics.
-
D.
Brooklynn Prince
Brooklynn Prince is an American child actress best known for her critically acclaimed breakout performance in the film "The Florida Project."
-
E.
A.R. Skuggs
A.R. Skuggs is the central protagonist of the film "Sugar Hill," around whom the story’s main events and conflicts revolve.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dffd6f88190a0f031ee90c6a7d2 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8af92a88190bd47f1a484f25eb1 |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:16 a.m.