Triple

T10837247
Position Surface form Disambiguated ID Type / Status
Subject Berta E255792 entity
Predicate hasDialect P4251 FINISHED
Object Shuru
Shuru is a dialect of the Berta language spoken by the Berta people of the Ethiopia–Sudan border region.
 E889288 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: Shuru | Statement: [Berta, hasDialect, Shuru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shuru
Context triple: [Berta, hasDialect, Shuru]
  • A. Mwanza
    Mwanza is a major port city in northwestern Tanzania, situated on the southern shores of Lake Victoria and serving as a key commercial and transport hub for the region.
  • B. Shaviklde
    Shaviklde is a prominent mountain peak in Georgia known as the highest summit of the Trialeti Range.
  • C. Shuar
    Shuar is an indigenous language of the Jivaroan family spoken by the Shuar people primarily in the Amazonian regions of Ecuador and Peru.
  • D. Chakari
    Chakari is a small mining and agricultural town located in the Mashonaland West Province of Zimbabwe.
  • E. Sarju
    Sarju is an alternate name for the Sarayu, a river historically associated with the ancient Indian city of Ayodhya and revered in Hindu tradition.
  • 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: Shuru
Triple: [Berta, hasDialect, Shuru]
Generated description
Shuru is a dialect of the Berta language spoken by the Berta people of the Ethiopia–Sudan border region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shuru
Target entity description: Shuru is a dialect of the Berta language spoken by the Berta people of the Ethiopia–Sudan border region.
  • A. Mwanza
    Mwanza is a major port city in northwestern Tanzania, situated on the southern shores of Lake Victoria and serving as a key commercial and transport hub for the region.
  • B. Shaviklde
    Shaviklde is a prominent mountain peak in Georgia known as the highest summit of the Trialeti Range.
  • C. Shuar
    Shuar is an indigenous language of the Jivaroan family spoken by the Shuar people primarily in the Amazonian regions of Ecuador and Peru.
  • D. Chakari
    Chakari is a small mining and agricultural town located in the Mashonaland West Province of Zimbabwe.
  • E. Sarju
    Sarju is an alternate name for the Sarayu, a river historically associated with the ancient Indian city of Ayodhya and revered in Hindu tradition.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d746ff70148190b844ab92d796af6c completed April 9, 2026, 6:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb12aae648190aa7c93cee60ae3ea completed April 14, 2026, 9:27 p.m.
NEDg Description generation batch_69dec2534728819095b3693120772da9 completed April 14, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_69dec79b1b548190a74312284f98551c completed April 14, 2026, 11:02 p.m.
Created at: April 8, 2026, 9:19 p.m.