Triple

T26635566
Position Surface form Disambiguated ID Type / Status
Subject Wilhelm Steinitz E668625 entity
Predicate opponent P437 FINISHED
Object Louis Paulsen
Louis Paulsen was a 19th-century German chess master renowned for his deep defensive play and contributions to opening theory, including the Paulsen Variation of the Sicilian Defense.
E1761557 NE FINISHED

How this triple was built (2 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: Louis Paulsen | Statement: [Wilhelm Steinitz, opponent, Louis Paulsen]
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: Louis Paulsen
Triple: [Wilhelm Steinitz, opponent, Louis Paulsen]
Generated description
Louis Paulsen was a 19th-century German chess master renowned for his deep defensive play and contributions to opening theory, including the Paulsen Variation of the Sicilian Defense.

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_69ee9d0024b8819090a7c8cf669a3b6c completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f616298eb48190913aefb29005cd67 completed May 2, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12535bcc8c81908e44018fdd7941ac completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a1254e770288190994c682cfe0f8c9d completed May 24, 2026, 1:31 a.m.
NED2 Entity disambiguation (via description) batch_6a12558ffcd08190b9a167ead908e052 completed May 24, 2026, 1:34 a.m.
Created at: April 27, 2026, 2:27 a.m.