Triple
T12331568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Do or Die |
E293971
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Belo Zero |
E976647
|
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: Belo Zero | Statement: [Do or Die, hasPart, Belo Zero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belo Zero Context triple: [Do or Die, hasPart, Belo Zero]
-
A.
Belo Zero
chosen
Belo Zero is an American rapper best known as a member of the Chicago hip hop group Do or Die.
-
B.
Back to Zero
"Back to Zero" is a song by The Rolling Stones from their 1986 album "Dirty Work."
-
C.
Too Low for Zero
Too Low for Zero is a 1983 Elton John studio album that marked a commercial and critical resurgence, featuring several of his best-known 1980s hits.
-
D.
Ceiling Zero
Ceiling Zero is a 1936 aviation drama film, directed by Howard Hawks and based on a play by former naval aviator Frank Wead, that focuses on the high-risk lives and camaraderie of airline pilots.
-
E.
Count Zero
Count Zero is a cyberpunk novel by William Gibson that continues the Sprawl trilogy, exploring artificial intelligence, cyberspace, and corporate power in a near-future dystopia.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f634ee08190b4f533505d402219 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62aa12f108190851c6958eb35ee5b |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:53 p.m.