Triple

T34787706
Position Surface form Disambiguated ID Type / Status
Subject Ljubičevo Equestrian Games E1002857 entity
Predicate locatedIn P40 FINISHED
Object Ljubičevo
Ljubičevo is a neighborhood of Požarevac in eastern Serbia, best known for its historic horse farm and annual equestrian games.
E2122634 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: Ljubičevo | Statement: [Ljubičevo Equestrian Games, locatedIn, Ljubičevo]
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: Ljubičevo
Triple: [Ljubičevo Equestrian Games, locatedIn, Ljubičevo]
Generated description
Ljubičevo is a neighborhood of Požarevac in eastern Serbia, best known for its historic horse farm and annual equestrian games.

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_69f76db47d408190a24fc7164439ea2d completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a604d608190af357dee743ba721 completed May 3, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37bcfbc3c081908362e285e372007f completed June 21, 2026, 10:29 a.m.
NEDg Description generation batch_6a37bda6c4408190a6f09442687dae28 completed June 21, 2026, 10:32 a.m.
NED2 Entity disambiguation (via description) batch_6a37bf374b7081908687f2997935411e completed June 21, 2026, 10:38 a.m.
Created at: May 3, 2026, 3:59 p.m.