Triple

T37155068
Position Surface form Disambiguated ID Type / Status
Subject Papp E920471 entity
Predicate hasNotableBearer P458 FINISHED
Object Mária Papp
Mária Papp is a notable individual who shares the Hungarian surname Papp, recognized for her contributions in her respective field.
E2218130 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: Mária Papp | Statement: [Papp, hasNotableBearer, Mária Papp]
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: Mária Papp
Triple: [Papp, hasNotableBearer, Mária Papp]
Generated description
Mária Papp is a notable individual who shares the Hungarian surname Papp, recognized for her contributions in her respective field.

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_69f76e9f87c08190b4c8f7fafbd8345a completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb308f838881908fedf011d62989ac completed May 6, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40360972188190b995fea5bf20faa5 completed June 27, 2026, 8:43 p.m.
NEDg Description generation batch_6a40367cb42c8190806545287c151139 completed June 27, 2026, 8:45 p.m.
NED2 Entity disambiguation (via description) batch_6a40384edcec8190a51c44c29a77de86 completed June 27, 2026, 8:53 p.m.
Created at: May 3, 2026, 4:15 p.m.