Triple

T6242367
Position Surface form Disambiguated ID Type / Status
Subject Cairo Metro Line 2 E139634 entity
Predicate hasStation P35 FINISHED
Object Masarra
Masarra is a passenger station on Cairo Metro’s Line 2 serving commuters in the Cairo metropolitan area.
 E578158 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: Masarra | Statement: [Cairo Metro Line 2, hasStation, Masarra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Masarra
Context triple: [Cairo Metro Line 2, hasStation, Masarra]
  • A. Masar
    Masar is a British Thoroughbred racehorse best known for winning the 2018 Epsom Derby for Godolphin.
  • B. Marwa
    Marwa is one of the two small hills in Mecca that Muslims traverse between during the ritual of Sa'i in the Hajj and Umrah pilgrimages.
  • C. Mesaieed
    Mesaieed is an industrial city in Qatar known for its major port facilities and petrochemical industries.
  • D. Masri
    Masri is a widely spoken modern Arabic dialect used primarily in Egypt, especially in everyday conversation and popular media.
  • E. Jabriya
    Jabriya is a residential suburb in Kuwait known for its mix of apartment buildings, schools, and local shops within the Hawalli Governorate.
  • 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: Masarra
Triple: [Cairo Metro Line 2, hasStation, Masarra]
Generated description
Masarra is a passenger station on Cairo Metro’s Line 2 serving commuters in the Cairo metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Masarra
Target entity description: Masarra is a passenger station on Cairo Metro’s Line 2 serving commuters in the Cairo metropolitan area.
  • A. Masar
    Masar is a British Thoroughbred racehorse best known for winning the 2018 Epsom Derby for Godolphin.
  • B. Marwa
    Marwa is one of the two small hills in Mecca that Muslims traverse between during the ritual of Sa'i in the Hajj and Umrah pilgrimages.
  • C. Mesaieed
    Mesaieed is an industrial city in Qatar known for its major port facilities and petrochemical industries.
  • D. Masri
    Masri is a widely spoken modern Arabic dialect used primarily in Egypt, especially in everyday conversation and popular media.
  • E. Jabriya
    Jabriya is a residential suburb in Kuwait known for its mix of apartment buildings, schools, and local shops within the Hawalli Governorate.
  • 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_69c008b1c5088190ae6de2555fc05ad8 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0631933488190838b424ec0fc2155 completed March 22, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20e0d62208190928bab473ca64417 completed March 24, 2026, 4:07 a.m.
NEDg Description generation batch_69c2158b7b8481909b64931c013cec27 completed March 24, 2026, 4:39 a.m.
NED2 Entity disambiguation (via description) batch_69c21600f90c8190840f84112f62e311 completed March 24, 2026, 4:41 a.m.
Created at: March 22, 2026, 4:23 p.m.