Triple

T8968315
Position Surface form Disambiguated ID Type / Status
Subject Sama-Bajau peoples E214194 entity
Predicate subgroup P10 FINISHED
Object Sama Bangingiʼ
Sama Bangingiʼ are a maritime Sama-Bajau subgroup of the southern Philippines and nearby regions, traditionally known for seafaring, fishing, and coastal trading.
E769632 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: Sama Bangingiʼ | Statement: [Sama-Bajau peoples, subgroup, Sama Bangingiʼ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sama Bangingiʼ
Context triple: [Sama-Bajau peoples, subgroup, Sama Bangingiʼ]
  • A. Matsigenka
    The Matsigenka are an Indigenous people of the Peruvian Amazon known for their forest-based subsistence lifestyle, distinct language, and rich shamanic and cosmological traditions.
  • B. Bongwe
    Bongwe is a dialect of the Duala language spoken by the Duala people of Cameroon.
  • C. Mundemba
    Mundemba is a town in southwestern Cameroon known as a gateway to the biodiverse Korup National Park.
  • D. Tena Kichwa
    Tena Kichwa is a variety of Amazonian Kichwa spoken around the town of Tena in Ecuador, closely associated with the Indigenous Kichwa communities of that region.
  • E. Gambiri Kati
    Gambiri Kati is an alternative name for the Tregami language, an Indo-Iranian language spoken in parts of eastern Afghanistan.
  • 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: Sama Bangingiʼ
Triple: [Sama-Bajau peoples, subgroup, Sama Bangingiʼ]
Generated description
Sama Bangingiʼ are a maritime Sama-Bajau subgroup of the southern Philippines and nearby regions, traditionally known for seafaring, fishing, and coastal trading.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sama Bangingiʼ
Target entity description: Sama Bangingiʼ are a maritime Sama-Bajau subgroup of the southern Philippines and nearby regions, traditionally known for seafaring, fishing, and coastal trading.
  • A. Matsigenka
    The Matsigenka are an Indigenous people of the Peruvian Amazon known for their forest-based subsistence lifestyle, distinct language, and rich shamanic and cosmological traditions.
  • B. Bongwe
    Bongwe is a dialect of the Duala language spoken by the Duala people of Cameroon.
  • C. Mundemba
    Mundemba is a town in southwestern Cameroon known as a gateway to the biodiverse Korup National Park.
  • D. Tena Kichwa
    Tena Kichwa is a variety of Amazonian Kichwa spoken around the town of Tena in Ecuador, closely associated with the Indigenous Kichwa communities of that region.
  • E. Gambiri Kati
    Gambiri Kati is an alternative name for the Tregami language, an Indo-Iranian language spoken in parts of eastern Afghanistan.
  • 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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6764aca48190a5e472d1b6841886 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc95cbc4c8190a3ac582f735eeb35 completed April 3, 2026, 2:06 p.m.
NEDg Description generation batch_69cfca41aed08190a5107597625e4b61 completed April 3, 2026, 2:10 p.m.
NED2 Entity disambiguation (via description) batch_69cfcaba165081908c7bbfb905356942 completed April 3, 2026, 2:12 p.m.
Created at: March 30, 2026, 7:01 p.m.