Triple

T17565664
Position Surface form Disambiguated ID Type / Status
Subject Medang Mataram period E427805 entity
Predicate hasRuler P5424 FINISHED
Object Tulodong
Tulodong was a 10th-century king of the Medang Mataram Kingdom in Central Java, Indonesia.
E1275296 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: Tulodong | Statement: [Medang Mataram period, hasRuler, Tulodong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tulodong
Context triple: [Medang Mataram period, hasRuler, Tulodong]
  • A. Guanito
    Guanito is a rural municipal district within the San Juan de la Maguana municipality in the San Juan Province of the Dominican Republic.
  • B. Talokan
    Talokan is a fictional underwater Mesoamerican-inspired kingdom ruled by Namor in the Marvel Cinematic Universe film "Black Panther: Wakanda Forever."
  • C. Maragondon
    Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
  • D. Tinglayan
    Tinglayan is a rural municipality in the Philippine province of Kalinga, known for its mountainous terrain, traditional Kalinga culture, and rice terraces.
  • E. Dinalungan
    Dinalungan is a coastal municipality in the province of Aurora in the Philippines, known for its rural landscapes and Pacific shoreline.
  • 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: Tulodong
Triple: [Medang Mataram period, hasRuler, Tulodong]
Generated description
Tulodong was a 10th-century king of the Medang Mataram Kingdom in Central Java, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tulodong
Target entity description: Tulodong was a 10th-century king of the Medang Mataram Kingdom in Central Java, Indonesia.
  • A. Guanito
    Guanito is a rural municipal district within the San Juan de la Maguana municipality in the San Juan Province of the Dominican Republic.
  • B. Talokan
    Talokan is a fictional underwater Mesoamerican-inspired kingdom ruled by Namor in the Marvel Cinematic Universe film "Black Panther: Wakanda Forever."
  • C. Maragondon
    Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
  • D. Tinglayan
    Tinglayan is a rural municipality in the Philippine province of Kalinga, known for its mountainous terrain, traditional Kalinga culture, and rice terraces.
  • E. Dinalungan
    Dinalungan is a coastal municipality in the province of Aurora in the Philippines, known for its rural landscapes and Pacific shoreline.
  • 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4592ce42c8190a54a0a328c5e8ffc completed April 19, 2026, 4:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01d29a14288190b5b665c5450b7c18 completed May 11, 2026, 12:59 p.m.
NEDg Description generation batch_6a01d43430d481909b07d8ecc09a185f completed May 11, 2026, 1:05 p.m.
NED2 Entity disambiguation (via description) batch_6a01d4c609fc819089147744317d4be3 completed May 11, 2026, 1:08 p.m.
Created at: April 10, 2026, 5:50 a.m.