Triple

T9495717
Position Surface form Disambiguated ID Type / Status
Subject Maadi E228998 entity
Predicate hasMetroStation P522 FINISHED
Object Maadi station
Maadi station is a Cairo Metro station serving the Maadi district in southern Cairo, Egypt.
 E802866 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: Maadi station | Statement: [Maadi, hasMetroStation, Maadi station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maadi station
Context triple: [Maadi, hasMetroStation, Maadi station]
  • A. Fabre station
    Fabre station is a Montreal Metro station on the Blue Line serving the Rosemont–La Petite-Patrie borough.
  • B. Olivais station
    Olivais station is a Lisbon Metro stop serving the Olivais neighborhood on the system’s Red Line.
  • C. Loria station
    Loria station is a stop on Buenos Aires’ Line A subway, serving passengers in the Balvanera neighborhood of the city.
  • D. Luzarches station
    Luzarches station is a railway terminus in the Val-d'Oise department of northern France, serving as the endpoint of a Transilien suburban line from Paris.
  • E. Oriente station
    Oriente station is a major multimodal transport hub in Lisbon, Portugal, serving as a key connection point for trains, metro, buses, and regional services.
  • 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: Maadi station
Triple: [Maadi, hasMetroStation, Maadi station]
Generated description
Maadi station is a Cairo Metro station serving the Maadi district in southern Cairo, Egypt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maadi station
Target entity description: Maadi station is a Cairo Metro station serving the Maadi district in southern Cairo, Egypt.
  • A. Lison station
    Lison station is a railway station in Normandy, France, serving as a regional junction on the French rail network.
  • B. Fabre station
    Fabre station is a Montreal Metro station on the Blue Line serving the Rosemont–La Petite-Patrie borough.
  • C. Olivais station
    Olivais station is a Lisbon Metro stop serving the Olivais neighborhood on the system’s Red Line.
  • D. Loria station
    Loria station is a stop on Buenos Aires’ Line A subway, serving passengers in the Balvanera neighborhood of the city.
  • E. Luzarches station
    Luzarches station is a railway terminus in the Val-d'Oise department of northern France, serving as the endpoint of a Transilien suburban line from Paris.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd95eb87b081908fc7255598cd9a24 completed April 1, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d34967881909980be6f1be80885 completed April 4, 2026, 3:24 p.m.
NEDg Description generation batch_69d13113474881909201282ce1385073 completed April 4, 2026, 3:41 p.m.
NED2 Entity disambiguation (via description) batch_69d131ade0588190bdf3cfdbbdd6df8e completed April 4, 2026, 3:43 p.m.
Created at: March 30, 2026, 7:56 p.m.