Triple

T10950422
Position Surface form Disambiguated ID Type / Status
Subject St. Pauli U-Bahn station E258710 entity
Predicate hasStationCode P1289 FINISHED
Object HHA: SP
HHA: SP is the station code used by Hamburger Hochbahn AG for the St. Pauli U-Bahn station in Hamburg, Germany.
 E894674 NE FINISHED

How this triple was built (4 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: HHA: SP | Statement: [St. Pauli U-Bahn station, hasStationCode, HHA: SP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HHA: SP
Context triple: [St. Pauli U-Bahn station, hasStationCode, HHA: SP]
  • A. HAA
    HAA is the Harvard Alumni Association, the organization that connects and serves Harvard University’s global community of alumni.
  • B. HH
    HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
  • C. HAP
    HAP is Apple's HomeKit Accessory Protocol, a communication standard that defines how smart home accessories securely interact with Apple devices and the Home app.
  • D. HPA
    HPA is the commonly used abbreviation for the Horse Protection Act, a U.S. federal law aimed at preventing the abusive practice of soring in show horses.
  • E. HPA
    HPA is the abbreviation for the Hamburg Port Authority, the organization responsible for managing and developing the Port of Hamburg in Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: HHA: SP
Triple: [St. Pauli U-Bahn station, hasStationCode, HHA: SP]
Generated description
HHA: SP is the station code used by Hamburger Hochbahn AG for the St. Pauli U-Bahn station in Hamburg, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HHA: SP
Target entity description: HHA: SP is the station code used by Hamburger Hochbahn AG for the St. Pauli U-Bahn station in Hamburg, Germany.
  • A. HAA
    HAA is the Harvard Alumni Association, the organization that connects and serves Harvard University’s global community of alumni.
  • B. HH
    HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
  • C. HAP
    HAP is Apple's HomeKit Accessory Protocol, a communication standard that defines how smart home accessories securely interact with Apple devices and the Home app.
  • D. HPA
    HPA is the commonly used abbreviation for the Horse Protection Act, a U.S. federal law aimed at preventing the abusive practice of soring in show horses.
  • E. HPA
    HPA is the abbreviation for the Hamburg Port Authority, the organization responsible for managing and developing the Port of Hamburg in Germany.
  • F. None of above. chosen

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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770ed2f1c819081ec58457f57889d completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c57038c819087671177c2ed5633 completed April 17, 2026, 1:57 p.m.
NEDg Description generation batch_69e24543bd2c8190a3c807baa76c30f6 completed April 17, 2026, 2:35 p.m.
NED2 Entity disambiguation (via description) batch_69e25d11ef24819091e730ae2416a058 completed April 17, 2026, 4:17 p.m.
Created at: April 8, 2026, 9:23 p.m.