Triple

T7901162
Position Surface form Disambiguated ID Type / Status
Subject Central Sama E183454 entity
Predicate hasDialect P4251 FINISHED
Object Tabawan Sama
Tabawan Sama is a dialect of the Central Sama language spoken by the Sama people, primarily associated with the island of Tabawan in the southern Philippines.
 E700461 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: Tabawan Sama | Statement: [Central Sama, hasDialect, Tabawan Sama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tabawan Sama
Context triple: [Central Sama, hasDialect, Tabawan Sama]
  • A. Sameba
    Sameba is the monumental main cathedral of the Georgian Orthodox Church in Tbilisi, renowned as one of the largest religious buildings in the Caucasus.
  • B. Tamalakaw
    Tamalakaw is a village in Taiwan known as one of the communities where the indigenous Puyuma language is traditionally spoken.
  • C. Wazhazhe
    Wazhazhe is the self-designation of the Osage people, a Native American nation originally from the central United States.
  • D. Sa Talaia
    Sa Talaia is the highest mountain on the island of Ibiza in Spain, offering panoramic views over the surrounding landscape and coastline.
  • E. Tabasaran
    Tabasaran is a Northeast Caucasian language spoken primarily by the Tabasaran people in southern Dagestan, Russia.
  • 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: Tabawan Sama
Triple: [Central Sama, hasDialect, Tabawan Sama]
Generated description
Tabawan Sama is a dialect of the Central Sama language spoken by the Sama people, primarily associated with the island of Tabawan in the southern Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tabawan Sama
Target entity description: Tabawan Sama is a dialect of the Central Sama language spoken by the Sama people, primarily associated with the island of Tabawan in the southern Philippines.
  • A. Sameba
    Sameba is the monumental main cathedral of the Georgian Orthodox Church in Tbilisi, renowned as one of the largest religious buildings in the Caucasus.
  • B. Tamalakaw
    Tamalakaw is a village in Taiwan known as one of the communities where the indigenous Puyuma language is traditionally spoken.
  • C. Wazhazhe
    Wazhazhe is the self-designation of the Osage people, a Native American nation originally from the central United States.
  • D. Sa Talaia
    Sa Talaia is the highest mountain on the island of Ibiza in Spain, offering panoramic views over the surrounding landscape and coastline.
  • E. Tabasaran
    Tabasaran is a Northeast Caucasian language spoken primarily by the Tabasaran people in southern Dagestan, Russia.
  • 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_69ca828d13088190b222be7aa9f9315c completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a3f4c2c81909ae70b0acf4729be completed March 31, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5bbd93348190883c6152f18f8214 completed March 31, 2026, 5:29 a.m.
NEDg Description generation batch_69cb7632cbbc819087107c8d2172a038 completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbb64eee408190a66cbd0cba3054b4 completed March 31, 2026, 11:55 a.m.
Created at: March 30, 2026, 5:02 p.m.