Triple

T32195463
Position Surface form Disambiguated ID Type / Status
Subject Plac Bankowy E822391 entity
Predicate hasNearbyBuilding P5648 FINISHED
Object Błękitny Wieżowiec
Błękitny Wieżowiec is a modern high-rise office building in central Warsaw, Poland, notable for its blue glass façade and prominent location on Plac Bankowy.
E1995640 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: Błękitny Wieżowiec | Statement: [Plac Bankowy, hasNearbyBuilding, Błękitny Wieżowiec]
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: Błękitny Wieżowiec
Triple: [Plac Bankowy, hasNearbyBuilding, Błękitny Wieżowiec]
Generated description
Błękitny Wieżowiec is a modern high-rise office building in central Warsaw, Poland, notable for its blue glass façade and prominent location on Plac Bankowy.

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_69f3490819cc81909bae1f8ce99423c5 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bb3795fc8190bfcb00d45aa887a1 completed May 3, 2026, 3:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0bec98288190b1480ba26b1e4eb6 completed June 14, 2026, 8:15 p.m.
NEDg Description generation batch_6a2f0ca5db008190a1de72d58c55d0bb completed June 14, 2026, 8:18 p.m.
NED2 Entity disambiguation (via description) batch_6a2f0e1ead7c8190bada929583412e06 completed June 14, 2026, 8:25 p.m.
Created at: May 1, 2026, 12:35 a.m.