Triple

T18313530
Position Surface form Disambiguated ID Type / Status
Subject Lonsdale Cup E438691 entity
Predicate notableWinner P2766 FINISHED
Object Enbihaar
Enbihaar is a high-class British-trained Thoroughbred racehorse best known as a top staying mare who excelled in long-distance Group races.
 E1318522 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: Enbihaar | Statement: [Lonsdale Cup, notableWinner, Enbihaar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Enbihaar
Context triple: [Lonsdale Cup, notableWinner, Enbihaar]
  • A. Banzebi
    Banzebi are a subgroup of the Nzebi people, an ethnic community primarily found in Central Africa, especially in Gabon and surrounding regions.
  • B. Darbenai
    Darbenai is a small town in western Lithuania, historically home to a Jewish community from which Zionist leader David Wolffsohn originated.
  • C. Baydhaba
    Baydhaba is a major city in southwestern Somalia that serves as the capital of the Bay region and an important political and commercial center.
  • D. Vabis
    Vabis was a Swedish automotive and engineering company that later merged to form Scania-Vabis, a predecessor of the modern Scania AB.
  • E. Akhras
    Akhras is a Syrian-origin family name best known for being the maiden surname of Asma al-Assad, the First Lady of Syria.
  • 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: Enbihaar
Triple: [Lonsdale Cup, notableWinner, Enbihaar]
Generated description
Enbihaar is a high-class British-trained Thoroughbred racehorse best known as a top staying mare who excelled in long-distance Group races.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Enbihaar
Target entity description: Enbihaar is a high-class British-trained Thoroughbred racehorse best known as a top staying mare who excelled in long-distance Group races.
  • A. Banzebi
    Banzebi are a subgroup of the Nzebi people, an ethnic community primarily found in Central Africa, especially in Gabon and surrounding regions.
  • B. Darbenai
    Darbenai is a small town in western Lithuania, historically home to a Jewish community from which Zionist leader David Wolffsohn originated.
  • C. Baydhaba
    Baydhaba is a major city in southwestern Somalia that serves as the capital of the Bay region and an important political and commercial center.
  • D. Vabis
    Vabis was a Swedish automotive and engineering company that later merged to form Scania-Vabis, a predecessor of the modern Scania AB.
  • E. Akhras
    Akhras is a Syrian-origin family name best known for being the maiden surname of Asma al-Assad, the First Lady of Syria.
  • 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5021b7e2c81908cd3b6684ab899f6 completed April 19, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03c4c1d8048190916dcc7146d15bc4 completed May 13, 2026, 12:24 a.m.
NEDg Description generation batch_6a03c66b72a0819081fe77b42060d6de completed May 13, 2026, 12:31 a.m.
NED2 Entity disambiguation (via description) batch_6a03c6f191b081909a0e65fa1d553b82 completed May 13, 2026, 12:33 a.m.
Created at: April 10, 2026, 10:36 a.m.