Triple

T25867280
Position Surface form Disambiguated ID Type / Status
Subject Alarchin Bridge E651651 entity
Predicate namedAfter P63 FINISHED
Object Alarchin Lane
Alarchin Lane is a historic street in Saint Petersburg, Russia, known for giving its name to the nearby Alarchin Bridge.
E1763060 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: Alarchin Lane | Statement: [Alarchin Bridge, namedAfter, Alarchin Lane]
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: Alarchin Lane
Triple: [Alarchin Bridge, namedAfter, Alarchin Lane]
Generated description
Alarchin Lane is a historic street in Saint Petersburg, Russia, known for giving its name to the nearby Alarchin Bridge.

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_69e7ab3a199c81909227cb964cacfe24 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f602d9b5c8819093aebab7bb20044d completed May 2, 2026, 1:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1262405cb08190a3421cb53c97993d completed May 24, 2026, 2:28 a.m.
NEDg Description generation batch_6a126440683881909b462092139a79cf completed May 24, 2026, 2:36 a.m.
NED2 Entity disambiguation (via description) batch_6a1264a5d7748190902dbe10317c00a8 completed May 24, 2026, 2:38 a.m.
Created at: April 22, 2026, 8:07 a.m.