Triple

T34610737
Position Surface form Disambiguated ID Type / Status
Subject Moika River embankment bridges E888723 entity
Predicate hasPart P35 FINISHED
Object Potseluev Bridge
Potseluev Bridge is a historic and picturesque cast-iron bridge in Saint Petersburg, Russia, known for its romantic associations and views over the Moika River.
E2111048 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: Potseluev Bridge | Statement: [Moika River embankment bridges, hasPart, Potseluev 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: Potseluev Bridge
Triple: [Moika River embankment bridges, hasPart, Potseluev Bridge]
Generated description
Potseluev Bridge is a historic and picturesque cast-iron bridge in Saint Petersburg, Russia, known for its romantic associations and views over the Moika River.

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_69f349d584e08190b40b9f6281ad50c4 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f721c63e9481908635d354b164c4db completed May 3, 2026, 10:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a376619fc048190b8886a5887c7b793 completed June 21, 2026, 4:18 a.m.
NEDg Description generation batch_6a37685268c08190ad38d914d9b64c58 completed June 21, 2026, 4:28 a.m.
NED2 Entity disambiguation (via description) batch_6a3768bbad8881908e539432566459dc completed June 21, 2026, 4:29 a.m.
Created at: May 1, 2026, 2:03 a.m.