Triple

T2481265
Position Surface form Disambiguated ID Type / Status
Subject Cairo Governorate E55820 entity
Predicate contains P35 FINISHED
Object Shubra
Shubra is a densely populated urban district in northern Cairo, Egypt, known for its vibrant commercial streets and diverse residential neighborhoods.
 E271409 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: Shubra | Statement: [Cairo Governorate, contains, Shubra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shubra
Context triple: [Cairo Governorate, contains, Shubra]
  • A. Umaria
    Umaria is a town and district headquarters in the central Indian state of Madhya Pradesh, known as a gateway to the nearby Bandhavgarh National Park.
  • B. Sabya
    Sabya is a city in southwestern Saudi Arabia located within the Jazan Region near the Red Sea coast.
  • C. Vashi
    Vashi is a major suburban railway station and commercial-residential hub in Navi Mumbai, India.
  • D. Jhelumi
    Jhelumi is a regional dialect of the Potohari language spoken primarily in and around the Jhelum area of Pakistan.
  • E. Uttara
    Uttara is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
  • 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: Shubra
Triple: [Cairo Governorate, contains, Shubra]
Generated description
Shubra is a densely populated urban district in northern Cairo, Egypt, known for its vibrant commercial streets and diverse residential neighborhoods.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shubra
Target entity description: Shubra is a densely populated urban district in northern Cairo, Egypt, known for its vibrant commercial streets and diverse residential neighborhoods.
  • A. Umaria
    Umaria is a town and district headquarters in the central Indian state of Madhya Pradesh, known as a gateway to the nearby Bandhavgarh National Park.
  • B. Sabya
    Sabya is a city in southwestern Saudi Arabia located within the Jazan Region near the Red Sea coast.
  • C. Vashi
    Vashi is a major suburban railway station and commercial-residential hub in Navi Mumbai, India.
  • D. Jhelumi
    Jhelumi is a regional dialect of the Potohari language spoken primarily in and around the Jhelum area of Pakistan.
  • E. Uttara
    Uttara is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
  • 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd161bf3c8190834502968180e9cf completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17b48d0881909442717d318a6f05 completed March 9, 2026, 6:55 p.m.
NEDg Description generation batch_69af1c4909888190aa6bc4f9731a8c68 completed March 9, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_69af1d2adea08190899d0dcd8d1c0bc7 completed March 9, 2026, 7:19 p.m.
Created at: March 6, 2026, 9:45 p.m.