Triple
T15535896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biggz |
E370340
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Mayhem |
E893787
|
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: Mayhem | Statement: [Biggz, associatedWith, Mayhem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mayhem Context triple: [Biggz, associatedWith, Mayhem]
-
A.
Mayhem
Mayhem is a professional ice hockey team based in Macon, Georgia, competing in the Southern Professional Hockey League.
-
B.
Mayhem
chosen
Mayhem is a pioneering Norwegian black metal band known for its influential yet controversial role in shaping the early 1990s black metal scene.
-
C.
Mayhem
Mayhem is a rockabilly- and blues-infused studio album by Irish singer Imelda May, showcasing her retro style and powerful vocals.
-
D.
Mayhem
Mayhem is a 2017 action-horror film in which Steven Yeun plays a corporate employee trapped in a quarantined office building where a virus unleashes violent chaos among workers.
-
E.
Godflesh
Godflesh is an influential English industrial metal band known for pioneering a harsh, mechanical fusion of metal, industrial, and experimental music.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442e327c8190b4b879c8a3cd38e3 |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d605b908190a18c63142c8bb854 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:06 a.m.