Triple

T21854617
Position Surface form Disambiguated ID Type / Status
Subject Elissa Landi E539590 entity
Predicate birthName P65 FINISHED
Object Elisabeth Marie Christine Kühnelt
Elisabeth Marie Christine Kühnelt, better known by her stage name Elissa Landi, was an Italian-born actress who gained fame in Hollywood films of the 1920s and 1930s.
E1629104 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: Elisabeth Marie Christine Kühnelt | Statement: [Elissa Landi, birthName, Elisabeth Marie Christine Kühnelt]
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: Elisabeth Marie Christine Kühnelt
Triple: [Elissa Landi, birthName, Elisabeth Marie Christine Kühnelt]
Generated description
Elisabeth Marie Christine Kühnelt, better known by her stage name Elissa Landi, was an Italian-born actress who gained fame in Hollywood films of the 1920s and 1930s.

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_69e0c47829648190bbe2d1d7033768ec completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0bd5ba9288190af962117124f6483 completed April 28, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc985aba481908d88ba63e510b04c completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcb9821dc81909eda37ccba173c7c completed May 22, 2026, 3:20 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcc2cd0108190a7531d50f6be2386 completed May 22, 2026, 3:23 a.m.
Created at: April 16, 2026, 6:56 p.m.