Triple

T26034895
Position Surface form Disambiguated ID Type / Status
Subject development of the Two Holy Mosques E647523 entity
Predicate location P40 FINISHED
Object Medina
Medina is Islam’s second holiest city, revered as the Prophet Muhammad’s burial place and home to the Prophet’s Mosque, a major center of pilgrimage and worship.
E28127 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: Medina | Statement: [development of the Two Holy Mosques, location, Medina]
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: Medina
Triple: [development of the Two Holy Mosques, location, Medina]
Generated description
Medina is Islam’s second holiest city, revered as the Prophet Muhammad’s burial place and home to the Prophet’s Mosque, a major center of pilgrimage and worship.

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_69e77e8c88f08190858c4c81bd2e1b9a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6061d145c8190bd51d69f0cdabd07 completed May 2, 2026, 2:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118f85aabc8190884c50b120dd878d completed May 23, 2026, 11:29 a.m.
NEDg Description generation batch_6a119053e3b0819092c8e62b5b4ae02a completed May 23, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a1190db5ab48190a5b902fee03abdde completed May 23, 2026, 11:34 a.m.
Created at: April 22, 2026, 9:07 a.m.