Triple

T38656126
Position Surface form Disambiguated ID Type / Status
Subject Lizzie Gottlieb E939894 entity
Predicate sibling P363 FINISHED
Object Nicolas Gottlieb
Nicolas Gottlieb is the brother of filmmaker Lizzie Gottlieb and a member of the Gottlieb family connected to the arts.
E2281153 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: Nicolas Gottlieb | Statement: [Lizzie Gottlieb, sibling, Nicolas Gottlieb]
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: Nicolas Gottlieb
Triple: [Lizzie Gottlieb, sibling, Nicolas Gottlieb]
Generated description
Nicolas Gottlieb is the brother of filmmaker Lizzie Gottlieb and a member of the Gottlieb family connected to the arts.

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_69f76ede49648190a48bfe47032a05a3 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcdbe8c56c8190ab80c9847566fa83 completed May 7, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4205ba2228819085cf5961574213e2 completed June 29, 2026, 5:42 a.m.
NEDg Description generation batch_6a4206c5417481909b8911ba28f91bf5 completed June 29, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_6a420754d65c8190910f5dfb5074fd3f completed June 29, 2026, 5:49 a.m.
Created at: May 3, 2026, 4:33 p.m.