Triple

T12986647
Position Surface form Disambiguated ID Type / Status
Subject Cheong E321784 entity
Predicate relatedRomanization P95894 FINISHED
Object Teo
Teo is a Korean surname and given name whose spelling reflects a particular system of romanizing Korean characters.
 E1015575 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: Teo | Statement: [Cheong, relatedRomanization, Teo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Teo
Context triple: [Cheong, relatedRomanization, Teo]
  • A. Teoh
    Teoh is a romanized Chinese surname, commonly used as a variant spelling of "Zhang" in Southeast Asia.
  • B. Teok
    Teok is a town in the Jorhat district of Assam, India, known as a local commercial and transportation hub in the region.
  • C. Tejo
    Tejo is the Portuguese name for the Tagus River, the longest river on the Iberian Peninsula that flows through Spain and Portugal into the Atlantic Ocean.
  • D. Theo
    Theo is a given name, often used as a short form of Theodore or related names, that has become a popular standalone first name in many countries.
  • E. Tino
    Tino is the commonly used nickname of former Major League Baseball first baseman Tino Martinez, best known for his years with the New York Yankees in the late 1990s and early 2000s.
  • 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: Teo
Triple: [Cheong, relatedRomanization, Teo]
Generated description
Teo is a Korean surname and given name whose spelling reflects a particular system of romanizing Korean characters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Teo
Target entity description: Teo is a Korean surname and given name whose spelling reflects a particular system of romanizing Korean characters.
  • A. Teoh
    Teoh is a romanized Chinese surname, commonly used as a variant spelling of "Zhang" in Southeast Asia.
  • B. Teok
    Teok is a town in the Jorhat district of Assam, India, known as a local commercial and transportation hub in the region.
  • C. Tejo
    Tejo is the Portuguese name for the Tagus River, the longest river on the Iberian Peninsula that flows through Spain and Portugal into the Atlantic Ocean.
  • D. Theo
    Theo is a given name, often used as a short form of Theodore or related names, that has become a popular standalone first name in many countries.
  • E. Tino
    Tino is the commonly used nickname of former Major League Baseball first baseman Tino Martinez, best known for his years with the New York Yankees in the late 1990s and early 2000s.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d9804b743c8190810dc5c14bc6d912 completed April 10, 2026, 10:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0f95c548190a6fc2c1ea98246c3 completed May 3, 2026, 3:28 a.m.
NEDg Description generation batch_69f6c34532148190a0c609ff085e359c completed May 3, 2026, 3:38 a.m.
NED2 Entity disambiguation (via description) batch_69f6c3c6b240819099310f50cc7eabca completed May 3, 2026, 3:40 a.m.
Created at: April 9, 2026, 8:40 p.m.