Triple

T24701470
Position Surface form Disambiguated ID Type / Status
Subject Groza E611754 entity
Predicate usedBy P260 FINISHED
Object Marius Groza
Marius Groza is an individual whose specific public profile or notable achievements are not clearly identifiable from the given information.
E1650261 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: Marius Groza | Statement: [Groza, usedBy, Marius Groza]
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: Marius Groza
Triple: [Groza, usedBy, Marius Groza]
Generated description
Marius Groza is an individual whose specific public profile or notable achievements are not clearly identifiable from the given information.

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_69e2c4d76d148190b58ad612467149a5 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40fe0833881909bf1b55eb10ff969 completed May 1, 2026, 2:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101bf5c76881909e4e33f9c1b90604 completed May 22, 2026, 9:03 a.m.
NEDg Description generation batch_6a1024f030f0819081ee3e587f5c9b44 completed May 22, 2026, 9:42 a.m.
NED2 Entity disambiguation (via description) batch_6a102541e25c819098a6de088ed849c7 completed May 22, 2026, 9:43 a.m.
Created at: April 18, 2026, 3:23 a.m.