Triple

T32166889
Position Surface form Disambiguated ID Type / Status
Subject Plac Trzech Krzyży E821604 entity
Predicate hasNearbyStreet P8235 FINISHED
Object Wiejska Street
Wiejska Street is a notable street in central Warsaw, Poland, known especially for housing the Polish Parliament complex and other important government institutions.
E2000949 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: Wiejska Street | Statement: [Plac Trzech Krzyży, hasNearbyStreet, Wiejska Street]
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: Wiejska Street
Triple: [Plac Trzech Krzyży, hasNearbyStreet, Wiejska Street]
Generated description
Wiejska Street is a notable street in central Warsaw, Poland, known especially for housing the Polish Parliament complex and other important government institutions.

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_69f3490699a48190bbef96b198e8fade completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6ba2089588190808706cc40fea7d6 completed May 3, 2026, 2:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3056eda90c819096c0245cc3bdc986 completed June 15, 2026, 7:47 p.m.
NEDg Description generation batch_6a3057bd1690819088277d98c9b78212 completed June 15, 2026, 7:51 p.m.
NED2 Entity disambiguation (via description) batch_6a305827285481909d8953d9e9e08831 completed June 15, 2026, 7:53 p.m.
Created at: May 1, 2026, 12:33 a.m.