Triple

T1221546
Position Surface form Disambiguated ID Type / Status
Subject Madura E26232 entity
Predicate hasMajorCity P316 FINISHED
Object Sampang
Sampang is a coastal city and regency capital on Madura Island in East Java, Indonesia, known for its traditional Madurese culture and agriculture-based economy.
 E143295 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: Sampang | Statement: [Madura, hasMajorCity, Sampang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sampang
Context triple: [Madura, hasMajorCity, Sampang]
  • A. Manggala
    Manggala was a Mongol prince of the 13th century, notable as one of the sons of the Yuan dynasty founder Kublai Khan.
  • B. Sukoró
    Sukoró is a village in Hungary’s Fejér County, known as a lakeside resort and recreational area on the northern shore of Lake Velence.
  • C. Bantia
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • D. Sasak
    Sasak is an Austronesian language spoken primarily by the Sasak people on the Indonesian island of Lombok.
  • E. Ranggawuni
    Ranggawuni was a 13th-century Javanese king of the Singhasari Kingdom, known for consolidating royal power and laying groundwork for the rise of later Javanese empires.
  • 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: Sampang
Triple: [Madura, hasMajorCity, Sampang]
Generated description
Sampang is a coastal city and regency capital on Madura Island in East Java, Indonesia, known for its traditional Madurese culture and agriculture-based economy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sampang
Target entity description: Sampang is a coastal city and regency capital on Madura Island in East Java, Indonesia, known for its traditional Madurese culture and agriculture-based economy.
  • A. Manggala
    Manggala was a Mongol prince of the 13th century, notable as one of the sons of the Yuan dynasty founder Kublai Khan.
  • B. Sukoró
    Sukoró is a village in Hungary’s Fejér County, known as a lakeside resort and recreational area on the northern shore of Lake Velence.
  • C. Bantia
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • D. Sasak
    Sasak is an Austronesian language spoken primarily by the Sasak people on the Indonesian island of Lombok.
  • E. Ranggawuni
    Ranggawuni was a 13th-century Javanese king of the Singhasari Kingdom, known for consolidating royal power and laying groundwork for the rise of later Javanese empires.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be206c108190bb8a5d44fc516c98 completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93bcdbbc8190a5eb1f4285faa8d4 completed March 7, 2026, 9:08 p.m.
NEDg Description generation batch_69ac9453f4488190a13ebabf3c8e07a5 completed March 7, 2026, 9:10 p.m.
NED2 Entity disambiguation (via description) batch_69ac952f74d48190b075919e0acd513d completed March 7, 2026, 9:14 p.m.
Created at: March 1, 2026, 7:47 p.m.