Triple

T23555022
Position Surface form Disambiguated ID Type / Status
Subject Omm El Misryeen E578161 entity
Predicate network P2637 FINISHED
Object Greater Cairo public transport network
The Greater Cairo public transport network is the extensive system of buses, minibuses, metro lines, and other mass transit services that connect Cairo and its surrounding urban areas.
E1595544 NE FINISHED

How this triple was built (2 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: Greater Cairo public transport network | Statement: [Omm El Misryeen, network, Greater Cairo public transport network]
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: Greater Cairo public transport network
Triple: [Omm El Misryeen, network, Greater Cairo public transport network]
Generated description
The Greater Cairo public transport network is the extensive system of buses, minibuses, metro lines, and other mass transit services that connect Cairo and its surrounding urban areas.

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_69e245fa93448190919cb04534560542 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1aed253788190ba75109af0e91b37 completed April 29, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f455dcc7081908e74459d465d4952 completed May 21, 2026, 5:48 p.m.
NEDg Description generation batch_6a0f4762e62c81908285cf6299f22250 completed May 21, 2026, 5:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f481aa71c8190bbbab462001d3586 completed May 21, 2026, 5:59 p.m.
Created at: April 17, 2026, 6:12 p.m.