Triple

T1388022
Position Surface form Disambiguated ID Type / Status
Subject Amir Sjarifuddin E29890 entity
Predicate familyName P18 FINISHED
Object Harahap
Harahap is an Indonesian Batak surname commonly associated with notable political and cultural figures.
 E159786 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: Harahap | Statement: [Amir Sjarifuddin, familyName, Harahap]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harahap
Context triple: [Amir Sjarifuddin, familyName, Harahap]
  • A. Haya
    Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • B. Hazaragi
    Hazaragi is a variety of Persian primarily spoken by the Hazara people of central Afghanistan and surrounding regions, distinguished by its unique phonology and significant Turkic and Mongolic influences.
  • C. Khashuri
    Khashuri is a town in central Georgia that serves as an important regional transport hub and gateway between eastern and western parts of the country.
  • D. Harauti
    Harauti is an Indo-Aryan dialect of the Rajasthani language spoken primarily in the Hadoti region of Rajasthan, India.
  • E. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • 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: Harahap
Triple: [Amir Sjarifuddin, familyName, Harahap]
Generated description
Harahap is an Indonesian Batak surname commonly associated with notable political and cultural figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harahap
Target entity description: Harahap is an Indonesian Batak surname commonly associated with notable political and cultural figures.
  • A. Haya
    Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • B. Hazaragi
    Hazaragi is a variety of Persian primarily spoken by the Hazara people of central Afghanistan and surrounding regions, distinguished by its unique phonology and significant Turkic and Mongolic influences.
  • C. Khashuri
    Khashuri is a town in central Georgia that serves as an important regional transport hub and gateway between eastern and western parts of the country.
  • D. Harauti
    Harauti is an Indo-Aryan dialect of the Rajasthani language spoken primarily in the Hadoti region of Rajasthan, India.
  • E. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • 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_69a498dc92f8819094a1108f8ac90f43 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c35ad578819090abf96222112bda completed March 1, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde2202208190894c3633c6a370d8 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acded052a88190945cf7a2af019c68 completed March 8, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_69acdf41eb5c819088f2203f33995ccb completed March 8, 2026, 2:30 a.m.
Created at: March 1, 2026, 7:59 p.m.