Triple

T11630956
Position Surface form Disambiguated ID Type / Status
Subject Hamburg City Hall E276395 entity
Predicate locatedNear P294 FINISHED
Object Binnenalster E241355 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: Binnenalster | Statement: [Hamburg City Hall, locatedNear, Binnenalster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Binnenalster
Context triple: [Hamburg City Hall, locatedNear, Binnenalster]
  • A. Binnenalster chosen
    Binnenalster is the smaller, inner section of Hamburg’s Alster lake, bordered by the city center and known for its scenic promenades and iconic fountain.
  • B. Schlachtensee
    Schlachtensee is a lake and popular recreational area in southwestern Berlin, known for swimming, walking trails, and its surrounding forested landscape.
  • C. Außenalster
    Außenalster is the larger, outer section of Hamburg’s Alster lake, known for sailing, rowing, and scenic waterfront paths near the city center.
  • D. Müggelsee
    Müggelsee is the largest lake in Berlin, Germany, known for its popular recreational areas and natural surroundings.
  • E. Schweriner See
    Schweriner See is a large lake in northern Germany that surrounds and characterizes the city of Schwerin, known for its scenic shores and historic lakeside castle.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a127b2688190ae3a340f851e834b completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f166403d6081908caa665433eaed53 completed April 29, 2026, 2 a.m.
Created at: April 8, 2026, 9:39 p.m.