Triple

T33690507
Position Surface form Disambiguated ID Type / Status
Subject Ghencea Cemetery E863164 entity
Predicate burialPlaceOf P196 FINISHED
Object Corneliu Mănescu
Corneliu Mănescu was a Romanian communist politician and diplomat who served as Romania’s foreign minister and later as president of the United Nations General Assembly.
E2076252 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: Corneliu Mănescu | Statement: [Ghencea Cemetery, burialPlaceOf, Corneliu Mănescu]
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: Corneliu Mănescu
Triple: [Ghencea Cemetery, burialPlaceOf, Corneliu Mănescu]
Generated description
Corneliu Mănescu was a Romanian communist politician and diplomat who served as Romania’s foreign minister and later as president of the United Nations General Assembly.

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_69f3498662b48190904442c39df84fb7 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fa838d0c8190a4f0d4fc6e7b6408 completed May 3, 2026, 7:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3689b9247c81908c891014af49ac91 completed June 20, 2026, 12:38 p.m.
NEDg Description generation batch_6a368ca6ad5c819081b2b498785e0b53 completed June 20, 2026, 12:50 p.m.
NED2 Entity disambiguation (via description) batch_6a368d4426888190aeabafa28cbe1b17 completed June 20, 2026, 12:53 p.m.
Created at: May 1, 2026, 1:43 a.m.