Triple

T2473151
Position Surface form Disambiguated ID Type / Status
Subject Miller Brewing Company E55022 entity
Predicate product P490 FINISHED
Object Miller 64
Miller 64 is a light, low-calorie American lager beer marketed as a lower-carb option for calorie-conscious drinkers.
 E270796 NE FINISHED

How this triple was built (4 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: Miller 64 | Statement: [Miller Brewing Company, product, Miller 64]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Miller 64
Context triple: [Miller Brewing Company, product, Miller 64]
  • A. Sauer
    Sauer is a German surname borne by various notable individuals in fields such as science, politics, and the arts.
  • B. Martz
    Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
  • C. Alvarez
    Alvarez is a common Spanish surname borne by numerous notable figures across fields such as science, sports, and the arts.
  • D. Yukon Striker
    Yukon Striker is a record-breaking dive roller coaster at Canada's Wonderland known for its 90-degree drop, underwater tunnel, and high speeds.
  • E. Speer
    Speer is a German surname most famously associated with Albert Speer, the Nazi architect and Minister of Armaments and War Production during World War II.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Miller 64
Triple: [Miller Brewing Company, product, Miller 64]
Generated description
Miller 64 is a light, low-calorie American lager beer marketed as a lower-carb option for calorie-conscious drinkers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Miller 64
Target entity description: Miller 64 is a light, low-calorie American lager beer marketed as a lower-carb option for calorie-conscious drinkers.
  • A. Sauer
    Sauer is a German surname borne by various notable individuals in fields such as science, politics, and the arts.
  • B. Martz
    Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
  • C. Alvarez
    Alvarez is a common Spanish surname borne by numerous notable figures across fields such as science, sports, and the arts.
  • D. Yukon Striker
    Yukon Striker is a record-breaking dive roller coaster at Canada's Wonderland known for its 90-degree drop, underwater tunnel, and high speeds.
  • E. Speer
    Speer is a German surname most famously associated with Albert Speer, the Nazi architect and Minister of Armaments and War Production during World War II.
  • F. None of above. chosen

Provenance (5 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_69ab49e279e88190ab10d7248aea9d11 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd149c10c819098ff75f176972c8b completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17a8d87c819084637958a5dc4028 completed March 9, 2026, 6:55 p.m.
NEDg Description generation batch_69af1b3bb8908190a48c6190f9f9a488 completed March 9, 2026, 7:10 p.m.
NED2 Entity disambiguation (via description) batch_69af1c404d248190b4444eaed46e63da completed March 9, 2026, 7:15 p.m.
Created at: March 6, 2026, 9:45 p.m.