Triple

T27360752
Position Surface form Disambiguated ID Type / Status
Subject U-Bahn station Warschauer Straße E685813 entity
Predicate locatedNear P294 FINISHED
Object RAW-Gelände cultural area
The RAW-Gelände cultural area is a former industrial railway complex in Berlin that has been transformed into a vibrant alternative cultural hub with clubs, art spaces, bars, and event venues.
 E1770163 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: RAW-Gelände cultural area | Statement: [U-Bahn station Warschauer Straße, locatedNear, RAW-Gelände cultural area]
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: RAW-Gelände cultural area
Triple: [U-Bahn station Warschauer Straße, locatedNear, RAW-Gelände cultural area]
Generated description
The RAW-Gelände cultural area is a former industrial railway complex in Berlin that has been transformed into a vibrant alternative cultural hub with clubs, art spaces, bars, and event venues.

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_69ef14887c288190931b8431fdbf53c4 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62c2202f48190a7d472609bdf822d completed May 2, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7db4e588190bfc10deebdec73c1 completed May 24, 2026, 7:25 a.m.
NEDg Description generation batch_6a12a87492b48190be0461fafe4d081d completed May 24, 2026, 7:27 a.m.
NED2 Entity disambiguation (via description) batch_6a12a926a67c819083713f0245b3e299 completed May 24, 2026, 7:30 a.m.
Created at: April 27, 2026, 11:53 a.m.