Triple

T22933964
Position Surface form Disambiguated ID Type / Status
Subject Southern Uma E569522 entity
Predicate hasName P744 FINISHED
Object Southern Uma NE NERFINISHED

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: Southern Uma | Statement: [Southern Uma, hasName, Southern Uma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Southern Uma
Context triple: [Southern Uma, hasName, Southern Uma]
  • A. Southern Uma chosen
    Southern Uma is a regional dialect of the Uma language spoken by a subset of Uma-speaking communities, distinguished by its own phonological and lexical features.
  • B. Northern Uma
    Northern Uma is a regional dialect of the Uma language spoken by communities in Central Sulawesi, Indonesia.
  • C. Central Sama
    Central Sama is an Austronesian language spoken by the Sama people of the southern Philippines and nearby regions, known for its role within the Sama–Bajaw language group.
  • D. South Upi
    South Upi is a rural municipality in the province of Maguindanao on the island of Mindanao in the southern Philippines.
  • E. Southern Yana
    Southern Yana is a now-extinct dialect of the Yana language once spoken by Indigenous people in northern California.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24590862c8190858f180ad302adab completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18134484c8190b7311606c17d058d completed April 29, 2026, 3:55 a.m.
Created at: April 17, 2026, 3:44 p.m.