Triple

T17001133
Position Surface form Disambiguated ID Type / Status
Subject Nürnberg-Dürrenhof station E412444 entity
Predicate hasStationCode P1289 FINISHED
Object NNDH
NNDH is the official station code used to identify Nürnberg-Dürrenhof railway station in Germany’s rail network.
 E1245297 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: NNDH | Statement: [Nürnberg-Dürrenhof station, hasStationCode, NNDH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NNDH
Context triple: [Nürnberg-Dürrenhof station, hasStationCode, NNDH]
  • A. NDH
    NDH was the fascist puppet state established by the Axis powers in World War II on the territory of occupied Croatia and Bosnia and Herzegovina.
  • B. NDD
    NDD is the common abbreviation for the Nagoya Diamond Dolphins, a professional basketball team based in Nagoya, Japan.
  • C. NNU
    NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
  • D. NNS
    NNS is the commonly used abbreviation for Newport News Shipbuilding, a major American shipyard known for constructing U.S. Navy aircraft carriers and submarines.
  • E. NHNN
    NHNN is the Vietnamese abbreviation for the State Bank of Vietnam, the country’s central bank responsible for monetary policy and financial regulation.
  • 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: NNDH
Triple: [Nürnberg-Dürrenhof station, hasStationCode, NNDH]
Generated description
NNDH is the official station code used to identify Nürnberg-Dürrenhof railway station in Germany’s rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NNDH
Target entity description: NNDH is the official station code used to identify Nürnberg-Dürrenhof railway station in Germany’s rail network.
  • A. NDH
    NDH was the fascist puppet state established by the Axis powers in World War II on the territory of occupied Croatia and Bosnia and Herzegovina.
  • B. NDD
    NDD is the common abbreviation for the Nagoya Diamond Dolphins, a professional basketball team based in Nagoya, Japan.
  • C. NNU
    NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
  • D. NNS
    NNS is the commonly used abbreviation for Newport News Shipbuilding, a major American shipyard known for constructing U.S. Navy aircraft carriers and submarines.
  • E. NHNN
    NHNN is the Vietnamese abbreviation for the State Bank of Vietnam, the country’s central bank responsible for monetary policy and financial regulation.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d37ec2b48190b4f997899d887ba8 completed April 18, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc1e2f708190999f6fab16fdabe8 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a0114d68c8481909111bfab22882bb2 completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0118ba68408190b242154c40461f21 completed May 10, 2026, 11:46 p.m.
Created at: April 10, 2026, 5:32 a.m.