Triple

T5168667
Position Surface form Disambiguated ID Type / Status
Subject Trans-Iranian Railway E116620 entity
Predicate passesThrough P225 FINISHED
Object Garmsar
Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
 E499638 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: Garmsar | Statement: [Trans-Iranian Railway, passesThrough, Garmsar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Garmsar
Context triple: [Trans-Iranian Railway, passesThrough, Garmsar]
  • A. Garve
    Garve is a small village and railway stop in the Scottish Highlands, situated on the route between Inverness and the west coast.
  • B. Hesselberg
    Hesselberg is a prominent hill in Bavaria, Germany, known as the highest elevation of the Franconian Alb region.
  • C. Eulachstadt
    Eulachstadt is a nickname for the Swiss city of Winterthur, reflecting its historical association with the Eulach River and its development as an important industrial and cultural center.
  • D. Drensteinfurt
    Drensteinfurt is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and location in the Münsterland region.
  • E. Kimry
    Kimry is a small Russian town on the Volga River known historically for its shoemaking industry and wooden architecture.
  • 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: Garmsar
Triple: [Trans-Iranian Railway, passesThrough, Garmsar]
Generated description
Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Garmsar
Target entity description: Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
  • A. Garve
    Garve is a small village and railway stop in the Scottish Highlands, situated on the route between Inverness and the west coast.
  • B. Hesselberg
    Hesselberg is a prominent hill in Bavaria, Germany, known as the highest elevation of the Franconian Alb region.
  • C. Eulachstadt
    Eulachstadt is a nickname for the Swiss city of Winterthur, reflecting its historical association with the Eulach River and its development as an important industrial and cultural center.
  • D. Drensteinfurt
    Drensteinfurt is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and location in the Münsterland region.
  • E. Kimry
    Kimry is a small Russian town on the Volga River known historically for its shoemaking industry and wooden architecture.
  • 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_69bd445ff97c81909a2615cc56235470 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd794dd9988190922e138f2a9a3c62 completed March 20, 2026, 4:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed93f33ac8190b2f60a8e95685bc8 completed March 21, 2026, 5:45 p.m.
NEDg Description generation batch_69beda0419108190862d028a14227e8a completed March 21, 2026, 5:48 p.m.
NED2 Entity disambiguation (via description) batch_69bedaa232ac81908c5ee2d4ba8cbcd7 completed March 21, 2026, 5:51 p.m.
Created at: March 20, 2026, 1:45 p.m.