Triple

T15157527
Position Surface form Disambiguated ID Type / Status
Subject Barbacoan languages E362116 entity
Predicate hasMember P10 FINISHED
Object Sindagua
Sindagua is an extinct Barbacoan language once spoken by indigenous communities in what is now southwestern Colombia.
E1141021 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: Sindagua | Statement: [Barbacoan languages, hasMember, Sindagua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sindagua
Context triple: [Barbacoan languages, hasMember, Sindagua]
  • A. Mvita
    Mvita is an alternative name for Kimvita, a historic Swahili settlement and cultural center on the coast of present-day Kenya.
  • B. Kalambo
    Kalambo is an agricultural research station site in the Lake Tanganyika region of Tanzania, known for supporting tropical crop and farming systems research.
  • C. Gwembe
    Gwembe is a small town in southern Zambia situated near the Zambezi Valley, historically associated with Tonga communities and resettlement related to the Kariba Dam.
  • D. Mangole
    Mangole is one of the principal islands of Indonesia’s Sula Islands archipelago in North Maluku Province.
  • E. Ongwediva
    Ongwediva is a growing town in northern Namibia known as an educational and commercial hub, hosting institutions like the University of Namibia’s campus and the annual Ongwediva Trade Fair.
  • 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: Sindagua
Triple: [Barbacoan languages, hasMember, Sindagua]
Generated description
Sindagua is an extinct Barbacoan language once spoken by indigenous communities in what is now southwestern Colombia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sindagua
Target entity description: Sindagua is an extinct Barbacoan language once spoken by indigenous communities in what is now southwestern Colombia.
  • A. Mvita
    Mvita is an alternative name for Kimvita, a historic Swahili settlement and cultural center on the coast of present-day Kenya.
  • B. Kalambo
    Kalambo is an agricultural research station site in the Lake Tanganyika region of Tanzania, known for supporting tropical crop and farming systems research.
  • C. Gwembe
    Gwembe is a small town in southern Zambia situated near the Zambezi Valley, historically associated with Tonga communities and resettlement related to the Kariba Dam.
  • D. Mangole
    Mangole is one of the principal islands of Indonesia’s Sula Islands archipelago in North Maluku Province.
  • E. Ongwediva
    Ongwediva is a growing town in northern Namibia known as an educational and commercial hub, hosting institutions like the University of Namibia’s campus and the annual Ongwediva Trade Fair.
  • 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_69d85a0759908190b8a051d2e2a1cbe6 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0060c62b08190bcdbd912d011d1ba completed April 15, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec88419108190860319a9bcab1eef completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec93f7c9c8190b9d1722180517d7c completed May 9, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_69fec9c518a08190b0ae7adad43a7f2c completed May 9, 2026, 5:44 a.m.
Created at: April 10, 2026, 3:08 a.m.