Triple

T4069611
Position Surface form Disambiguated ID Type / Status
Subject Mam E86612 entity
Predicate hasDialect P4251 FINISHED
Object Northern Mam
Northern Mam is a Mayan language variety spoken primarily in the highland regions of Guatemala by Mam indigenous communities.
 E411183 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: Northern Mam | Statement: [Mam, hasDialect, Northern Mam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Northern Mam
Context triple: [Mam, hasDialect, Northern Mam]
  • A. The Great North
    The Great North is an animated sitcom that follows the eccentric Tobin family as they navigate life in the wilds of Alaska.
  • B. Snowy Tundra
    Snowy Tundra is a cold, snow-covered biome in Minecraft characterized by flat, icy terrain, sparse vegetation, and frequent snowfall.
  • C. Winterpeg
    Winterpeg is a humorous nickname for Winnipeg, Canada, referencing the city's notoriously long, cold, and snowy winters.
  • D. Nanooks
    Nanooks is the nickname for the University of Alaska Fairbanks athletic teams, representing the school in NCAA competition.
  • E. Wabush
    Wabush is a small mining town in western Labrador, Canada, known historically for its iron ore operations and proximity to Labrador City.
  • 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: Northern Mam
Triple: [Mam, hasDialect, Northern Mam]
Generated description
Northern Mam is a Mayan language variety spoken primarily in the highland regions of Guatemala by Mam indigenous communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Northern Mam
Target entity description: Northern Mam is a Mayan language variety spoken primarily in the highland regions of Guatemala by Mam indigenous communities.
  • A. The Great North
    The Great North is an animated sitcom that follows the eccentric Tobin family as they navigate life in the wilds of Alaska.
  • B. Snowy Tundra
    Snowy Tundra is a cold, snow-covered biome in Minecraft characterized by flat, icy terrain, sparse vegetation, and frequent snowfall.
  • C. Winterpeg
    Winterpeg is a humorous nickname for Winnipeg, Canada, referencing the city's notoriously long, cold, and snowy winters.
  • D. Nanooks
    Nanooks is the nickname for the University of Alaska Fairbanks athletic teams, representing the school in NCAA competition.
  • E. Wabush
    Wabush is a small mining town in western Labrador, Canada, known historically for its iron ore operations and proximity to Labrador City.
  • 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_69aed93ebe448190a1f1686e28740ac9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbfa45c88190b7b13b35de816378 completed March 9, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562b6eb708190a7f60192d8df9a27 completed March 14, 2026, 1:29 p.m.
NEDg Description generation batch_69b5668984988190bb4239df9e283142 completed March 14, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_69b566ea87f88190ad03e548de53553f completed March 14, 2026, 1:47 p.m.
Created at: March 9, 2026, 3:38 p.m.