Triple

T18377590
Position Surface form Disambiguated ID Type / Status
Subject 1896 Olympics men’s 100 metre freestyle E446356 entity
Predicate silverMedalist P15191 FINISHED
Object Otto Herschmann
Otto Herschmann was an Austrian Jewish athlete and sports official who notably excelled in both swimming and fencing, becoming one of the few people to win Olympic medals in two different sports.
E1995948 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: Otto Herschmann | Statement: [1896 Olympics men’s 100 metre freestyle, silverMedalist, Otto Herschmann]
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: Otto Herschmann
Triple: [1896 Olympics men’s 100 metre freestyle, silverMedalist, Otto Herschmann]
Generated description
Otto Herschmann was an Austrian Jewish athlete and sports official who notably excelled in both swimming and fencing, becoming one of the few people to win Olympic medals in two different sports.

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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5179919c881908d55ea24f93c5827 completed April 19, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0ba602a881909d21bccb6d52b7ee completed June 14, 2026, 8:14 p.m.
NEDg Description generation batch_6a2f0c75144c8190bd305d2b1c10a6e3 completed June 14, 2026, 8:17 p.m.
NED2 Entity disambiguation (via description) batch_6a2f2edbc2f0819097f1dcfafe9e442c completed June 14, 2026, 10:44 p.m.
Created at: April 10, 2026, 10:45 a.m.