Triple

T30762903
Position Surface form Disambiguated ID Type / Status
Subject Daniel Kehlmann E783282 entity
Predicate hasParent P120 FINISHED
Object Michael Kehlmann
Michael Kehlmann was an Austrian television and film director and screenwriter, known for his extensive work in German-language TV productions and as the father of writer Daniel Kehlmann.
E1933020 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: Michael Kehlmann | Statement: [Daniel Kehlmann, hasParent, Michael Kehlmann]
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: Michael Kehlmann
Triple: [Daniel Kehlmann, hasParent, Michael Kehlmann]
Generated description
Michael Kehlmann was an Austrian television and film director and screenwriter, known for his extensive work in German-language TV productions and as the father of writer Daniel Kehlmann.

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_69f224b047f48190b4f5efeb7ee97b37 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68fba02708190a1d0392453790fd8 completed May 2, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbd289288190941bd73bdebb9481 completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bc80ccc881909a65070a3201c7a2 completed June 10, 2026, 1:23 a.m.
NED2 Entity disambiguation (via description) batch_6a28bd11752881909989925c16498f98 completed June 10, 2026, 1:25 a.m.
Created at: April 29, 2026, 8:39 p.m.