Triple

T26004909
Position Surface form Disambiguated ID Type / Status
Subject Saint Petersburg street network E646730 entity
Predicate hasComponent P35 FINISHED
Object Bolsheokhtinsky Bridge
The Bolsheokhtinsky Bridge is a historic steel truss bridge over the Neva River in Saint Petersburg, Russia, notable for its distinctive towers and role as a key transport link in the city.
E1723504 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: Bolsheokhtinsky Bridge | Statement: [Saint Petersburg street network, hasComponent, Bolsheokhtinsky Bridge]
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: Bolsheokhtinsky Bridge
Triple: [Saint Petersburg street network, hasComponent, Bolsheokhtinsky Bridge]
Generated description
The Bolsheokhtinsky Bridge is a historic steel truss bridge over the Neva River in Saint Petersburg, Russia, notable for its distinctive towers and role as a key transport link in the city.

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_69e77e89d5848190b54352cdb74f6029 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6057964948190b3ecab50a47a5e7c completed May 2, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ae95964881908c5ab6f3a95f528a completed May 23, 2026, 1:41 p.m.
NEDg Description generation batch_6a11af355d588190a5f72f8c7d6e8db8 completed May 23, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_6a11afa0df548190a099d227f233ee94 completed May 23, 2026, 1:46 p.m.
Created at: April 22, 2026, 9 a.m.