Triple

T18501451
Position Surface form Disambiguated ID Type / Status
Subject Ostring stop E452078 entity
Predicate hasName P744 FINISHED
Object Haltestelle Ostring
Haltestelle Ostring is a public transit stop, likely serving buses or trams, located in a German-speaking area.
E1327599 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: Haltestelle Ostring | Statement: [Ostring stop, hasName, Haltestelle Ostring]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haltestelle Ostring
Context triple: [Ostring stop, hasName, Haltestelle Ostring]
  • A. Orange Street station
    Orange Street station is a stop on the Newark Light Rail system in Newark, New Jersey, serving local commuters with light rail transit connections.
  • B. Leeland Road station
    Leeland Road station is a Virginia Railway Express commuter rail stop serving suburban passengers on the Fredericksburg Line in Stafford County, Virginia.
  • C. Strand station
    Strand station was a former name of what is now Charing Cross Underground station on the London Underground network.
  • D. Queen Lane station
    Queen Lane station is a SEPTA Regional Rail stop in Philadelphia, Pennsylvania, serving the Chestnut Hill West Line.
  • E. Ingleside Road station
    Ingleside Road station is a light rail stop on The Tide system in Norfolk, Virginia, serving nearby residential and commercial areas.
  • 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: Haltestelle Ostring
Triple: [Ostring stop, hasName, Haltestelle Ostring]
Generated description
Haltestelle Ostring is a public transit stop, likely serving buses or trams, located in a German-speaking area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Haltestelle Ostring
Target entity description: Haltestelle Ostring is a public transit stop, likely serving buses or trams, located in a German-speaking area.
  • A. Orange Street station
    Orange Street station is a stop on the Newark Light Rail system in Newark, New Jersey, serving local commuters with light rail transit connections.
  • B. Leeland Road station
    Leeland Road station is a Virginia Railway Express commuter rail stop serving suburban passengers on the Fredericksburg Line in Stafford County, Virginia.
  • C. Strand station
    Strand station was a former name of what is now Charing Cross Underground station on the London Underground network.
  • D. Queen Lane station
    Queen Lane station is a SEPTA Regional Rail stop in Philadelphia, Pennsylvania, serving the Chestnut Hill West Line.
  • E. Ingleside Road station
    Ingleside Road station is a light rail stop on The Tide system in Norfolk, Virginia, serving nearby residential and commercial areas.
  • 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_69d8d3855d50819097fc8561b0299dd9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e532c43de48190b49b87c1bb591016 completed April 19, 2026, 7:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a047141e8208190b240a11ae3b02ec0 completed May 13, 2026, 12:40 p.m.
NEDg Description generation batch_6a04738415508190945eec50944d96e9 completed May 13, 2026, 12:50 p.m.
NED2 Entity disambiguation (via description) batch_6a04746a380c819097df59bdbce0f6f6 completed May 13, 2026, 12:54 p.m.
Created at: April 10, 2026, 11:36 a.m.