Triple

T37325473
Position Surface form Disambiguated ID Type / Status
Subject Berlin Romantic circle E926588 entity
Predicate hasMember P10 FINISHED
Object Henriette Herz
Henriette Herz was a prominent German-Jewish intellectual and salonnière of the late 18th and early 19th centuries, known for hosting influential literary and philosophical gatherings in Berlin.
E2228054 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: Henriette Herz | Statement: [Berlin Romantic circle, hasMember, Henriette Herz]
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: Henriette Herz
Triple: [Berlin Romantic circle, hasMember, Henriette Herz]
Generated description
Henriette Herz was a prominent German-Jewish intellectual and salonnière of the late 18th and early 19th centuries, known for hosting influential literary and philosophical gatherings in Berlin.

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_69f76eb386d88190a8d511aa11540dfc completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5b657cf0819097901dd9382b2ae2 completed May 6, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a408c1ecfe48190889f9ae5c25299ea completed June 28, 2026, 2:51 a.m.
NEDg Description generation batch_6a408d2e0fa08190b1cf565f595ed784 completed June 28, 2026, 2:55 a.m.
NED2 Entity disambiguation (via description) batch_6a408d9a88588190acbfd23182ba0353 completed June 28, 2026, 2:57 a.m.
Created at: May 3, 2026, 4:16 p.m.