Triple

T27768027
Position Surface form Disambiguated ID Type / Status
Subject Georgenkirchplatz E701656 entity
Predicate hasTransportationConnection P1298 FINISHED
Object Berlin Hackescher Markt station
Berlin Hackescher Markt station is a central Berlin S-Bahn railway station near Alexanderplatz, serving as a key hub for regional and urban rail connections in the city’s Mitte district.
E1882460 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: Berlin Hackescher Markt station | Statement: [Georgenkirchplatz, hasTransportationConnection, Berlin Hackescher Markt station]
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: Berlin Hackescher Markt station
Triple: [Georgenkirchplatz, hasTransportationConnection, Berlin Hackescher Markt station]
Generated description
Berlin Hackescher Markt station is a central Berlin S-Bahn railway station near Alexanderplatz, serving as a key hub for regional and urban rail connections in the city’s Mitte district.

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_69ef6a52fa708190934a32308d2c92dc completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f6379463488190b5d5cc8fa944f1fe completed May 2, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa490bfc81908ba7ee36008e89dd completed June 8, 2026, 11:40 a.m.
NEDg Description generation batch_6a26b0582c708190938ca701d8851333 completed June 8, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_6a26bbd97f988190a8542548278aa52a completed June 8, 2026, 12:55 p.m.
Created at: April 27, 2026, 4:32 p.m.