Triple

T32370424
Position Surface form Disambiguated ID Type / Status
Subject Karl Haas E827118 entity
Predicate givenName P17 FINISHED
Object Karl
Karl is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries and related to the English name Charles.
E79216 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: Karl | Statement: [Karl Haas, givenName, Karl]
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: Karl
Triple: [Karl Haas, givenName, Karl]
Generated description
Karl is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries and related to the English name Charles.

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_69f349166d548190887b412fe908e2f4 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c128dc208190ba47578a71791740 completed May 3, 2026, 3:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a344efd6eec8190ac25ef69f58c5b23 completed June 18, 2026, 8:03 p.m.
NEDg Description generation batch_6a344f87053881908eb14e42d7af5ee9 completed June 18, 2026, 8:05 p.m.
NED2 Entity disambiguation (via description) batch_6a34515b17d88190b03116bc02a4711f completed June 18, 2026, 8:13 p.m.
Created at: May 1, 2026, 12:50 a.m.