Triple

T33677184
Position Surface form Disambiguated ID Type / Status
Subject Teréz körút E862791 entity
Predicate hasNameInEnglish P3437 FINISHED
Object Theresa Boulevard
Theresa Boulevard is the English name for Teréz körút, a major thoroughfare in central Budapest, Hungary.
 E2296237 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: Theresa Boulevard | Statement: [Teréz körút, hasNameInEnglish, Theresa Boulevard]
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: Theresa Boulevard
Triple: [Teréz körút, hasNameInEnglish, Theresa Boulevard]
Generated description
Theresa Boulevard is the English name for Teréz körút, a major thoroughfare in central Budapest, Hungary.

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_69f34985885c8190914322f492e04703 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fa4078a88190a0851bdcae68f2ea completed May 3, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a82520b75508190915e43d6a22d03d1 completed Aug. 17, 2026, 12:12 a.m.
NEDg Description generation batch_6a82525cfb888190af4ccda2a0177810 completed Aug. 17, 2026, 12:14 a.m.
NED2 Entity disambiguation (via description) batch_6a82528c374081908427eab7e1e931ce completed Aug. 17, 2026, 12:15 a.m.
Created at: May 1, 2026, 1:43 a.m.