Triple
T8176248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | God Did |
E190941
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | Bounty Killer |
E376358
|
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: Bounty Killer | Statement: [God Did, featuresArtist, Bounty Killer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bounty Killer Context triple: [God Did, featuresArtist, Bounty Killer]
-
A.
Bounty Killer
chosen
Bounty Killer is a Jamaican dancehall and reggae deejay known for his gritty delivery, influential 1990s hits, and role in shaping hardcore dancehall music.
-
B.
Bounty
Bounty is a popular Procter & Gamble paper towel brand known for its high absorbency and durability.
-
C.
Zabivaka
Zabivaka is the wolf character that served as the official mascot for major international football tournaments hosted by Russia, including the 2018 FIFA World Cup.
-
D.
The Rockville Slayer
The Rockville Slayer is a low-budget independent horror film featuring Joe Estevez in a story about a small town terrorized by a brutal serial killer.
-
E.
The Big Kill
The Big Kill is a hardboiled crime novel featuring private investigator Mike Hammer, written by American mystery author Mickey Spillane.
- 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_69ca82c1c0a08190bf8692b4d91a03ca |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4ab8295081909a450fcaa34f6ec6 |
completed | March 31, 2026, 4:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbf75bf2481908d585f7017be36a5 |
completed | April 1, 2026, 6:47 a.m. |
Created at: March 30, 2026, 5:40 p.m.