Triple

T10775772
Position Surface form Disambiguated ID Type / Status
Subject western Sudan E254192 entity
Predicate hasLanguage P15 FINISHED
Object Masalit language E247373 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: Masalit language | Statement: [western Sudan, hasLanguage, Masalit language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masalit language
Context triple: [western Sudan, hasLanguage, Masalit language]
  • A. Masalit language chosen
    Masalit language is an Eastern Sudanic language spoken primarily by the Masalit people in western Sudan and eastern Chad.
  • B. Lasalimu language
    The Lasalimu language is an Austronesian language spoken by a small community on Buton Island in Southeast Sulawesi, Indonesia.
  • C. Saliba language
    The Saliba language is an Oceanic language spoken in Papua New Guinea, particularly in the Milne Bay Province, and is known for its role in local maritime and village communication.
  • D. Mararit language
    The Mararit language is a lesser-known Nilo-Saharan language spoken by the Mararit people in parts of Chad and Sudan.
  • E. Malasanga language
    The Malasanga language is an Oceanic language spoken in Papua New Guinea, belonging to the Kula–Malasanga subgroup of the Austronesian language family.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7329cc6c881908f827edff941d456 completed April 9, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69de238ff88881908676d38dca041cb4 completed April 14, 2026, 11:22 a.m.
Created at: April 8, 2026, 9:16 p.m.