Triple

T6688647
Position Surface form Disambiguated ID Type / Status
Subject Aralle-Tabulahan language E152165 entity
Predicate hasDialect P4251 FINISHED
Object Aralle
Aralle is a dialect of the Aralle-Tabulahan language spoken by an indigenous community in West Sulawesi, Indonesia.
E610791 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: Aralle | Statement: [Aralle-Tabulahan language, hasDialect, Aralle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aralle
Context triple: [Aralle-Tabulahan language, hasDialect, Aralle]
  • A. Arakoon
    Arakoon is a small coastal locality in New South Wales, Australia, known for its beaches and the historic Trial Bay Gaol.
  • B. Arvieu
    Arvieu is a rural commune in the Aveyron department of southern France, known for its scenic setting on the Lévézou plateau near major lakes and its traditional agricultural character.
  • C. Arlay
    Arlay is a historic locality in eastern France that served as the principal seat of the noble House of Chalon-Arlay.
  • D. Arudy
    Arudy is a small commune in southwestern France, known as a gateway village to the Ossau Valley in the Pyrenees.
  • E. Arlanxeo
    Arlanxeo is a global synthetic rubber company specializing in high-performance elastomer products for the automotive, construction, and industrial sectors.
  • 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: Aralle
Triple: [Aralle-Tabulahan language, hasDialect, Aralle]
Generated description
Aralle is a dialect of the Aralle-Tabulahan language spoken by an indigenous community in West Sulawesi, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Aralle
Target entity description: Aralle is a dialect of the Aralle-Tabulahan language spoken by an indigenous community in West Sulawesi, Indonesia.
  • A. Arakoon
    Arakoon is a small coastal locality in New South Wales, Australia, known for its beaches and the historic Trial Bay Gaol.
  • B. Arvieu
    Arvieu is a rural commune in the Aveyron department of southern France, known for its scenic setting on the Lévézou plateau near major lakes and its traditional agricultural character.
  • C. Arlay
    Arlay is a historic locality in eastern France that served as the principal seat of the noble House of Chalon-Arlay.
  • D. Arudy
    Arudy is a small commune in southwestern France, known as a gateway village to the Ossau Valley in the Pyrenees.
  • E. Arlanxeo
    Arlanxeo is a global synthetic rubber company specializing in high-performance elastomer products for the automotive, construction, and industrial sectors.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14feb28819097bc157df8a2f96e completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7b31fa0819089c4debbbbce9d22 completed March 27, 2026, 9:33 p.m.
NEDg Description generation batch_69c6f8d27d388190816cfeefbe1519d8 completed March 27, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69c6f9729d7881908f3c396690ffcae8 completed March 27, 2026, 9:41 p.m.
Created at: March 27, 2026, 2:04 p.m.