Triple

T4606311
Position Surface form Disambiguated ID Type / Status
Subject Bangsamoro Autonomous Region in Muslim Mindanao E100445 entity
Predicate hasProvince P285 FINISHED
Object Sulu
Sulu is an island province in the southern Philippines known for its predominantly Muslim population, rich Tausug culture, and historical role as the center of the Sultanate of Sulu.
 E458383 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: Sulu | Statement: [Bangsamoro Autonomous Region in Muslim Mindanao, hasProvince, Sulu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sulu
Context triple: [Bangsamoro Autonomous Region in Muslim Mindanao, hasProvince, Sulu]
  • A. Phusro
    Phusro is a coal-mining and industrial town in the Bokaro district of Jharkhand, India.
  • B. Luyana
    Luyana is a Bantu language of southwestern Africa that historically served as a prestige and source language for the development of the Lozi language.
  • C. Shapuri
    Shapuri is a regional dialect of the Lahnda (Western Punjabi) language spoken in parts of Pakistan’s Punjab region.
  • D. Taif
    Taif is a city in western Saudi Arabia known for its cool climate, rose cultivation, and historical significance as a summer resort and cultural center.
  • E. Kangar
    Kangar is the main administrative and commercial center of the Malaysian state of Perlis.
  • 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: Sulu
Triple: [Bangsamoro Autonomous Region in Muslim Mindanao, hasProvince, Sulu]
Generated description
Sulu is an island province in the southern Philippines known for its predominantly Muslim population, rich Tausug culture, and historical role as the center of the Sultanate of Sulu.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sulu
Target entity description: Sulu is an island province in the southern Philippines known for its predominantly Muslim population, rich Tausug culture, and historical role as the center of the Sultanate of Sulu.
  • A. Phusro
    Phusro is a coal-mining and industrial town in the Bokaro district of Jharkhand, India.
  • B. Luyana
    Luyana is a Bantu language of southwestern Africa that historically served as a prestige and source language for the development of the Lozi language.
  • C. Shapuri
    Shapuri is a regional dialect of the Lahnda (Western Punjabi) language spoken in parts of Pakistan’s Punjab region.
  • D. Taif
    Taif is a city in western Saudi Arabia known for its cool climate, rose cultivation, and historical significance as a summer resort and cultural center.
  • E. Kangar
    Kangar is the main administrative and commercial center of the Malaysian state of Perlis.
  • 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_69bd43cce1e08190a07d53af6a9b6c24 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd599b1f0881909fd693b81ff44f98 completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa725c048190af9eea074197fa32 completed March 21, 2026, 1:54 a.m.
NEDg Description generation batch_69bdfd26fbe08190aa44c4a1cbd83f6a completed March 21, 2026, 2:06 a.m.
NED2 Entity disambiguation (via description) batch_69bdfdc4156081909bf99ae7f72fde23 completed March 21, 2026, 2:09 a.m.
Created at: March 20, 2026, 1:12 p.m.