Triple

T25456698

Position	Surface form	Disambiguated ID	Type / Status
Subject	مكة المكرمة	`E637931`	entity
Predicate	ترتبط بقطار	`P76977`	FINISHED
Object	قطار الحرمين السريع قطار الحرمين السريع هو مشروع سكة حديدية عالية السرعة يربط بين المدن المقدسة في المملكة العربية السعودية، بما في ذلك مكة المكرمة والمدينة المنورة، لتسهيل تنقل الحجاج والمعتمرين.	`E1681254`	NE FINISHED

How this triple was built (3 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: قطار الحرمين السريع | Statement: [مكة المكرمة, ترتبط بقطار, قطار الحرمين السريع]

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: قطار الحرمين السريع
Triple: [مكة المكرمة, ترتبط بقطار, قطار الحرمين السريع]

Generated description

قطار الحرمين السريع هو مشروع سكة حديدية عالية السرعة يربط بين المدن المقدسة في المملكة العربية السعودية، بما في ذلك مكة المكرمة والمدينة المنورة، لتسهيل تنقل الحجاج والمعتمرين.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: ترتبط بقطار
Context triple: [مكة المكرمة, ترتبط بقطار, قطار الحرمين السريع]

A. مرتبطب
Indicates a relationship of being connected, associated, or related to something or someone.
B. повʼязанеЗ
Indicates a general association or connection between one entity and another.
C. trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
D. connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
E. relatedRailroad chosen
Indicates that there is an association or connection between an entity and a specific railroad, such as ownership, operation, service, or historical linkage.
F. None of above.

Provenance (6 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_69e75db8bab08190baca80b4a8c315fd`	completed	April 21, 2026, 11:21 a.m.
NER	Named-entity recognition	`batch_69f5f72756748190aa315cc00882a798`	completed	May 2, 2026, 1:07 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a1089b29dc88190b22aae8b224368a5`	completed	May 22, 2026, 4:52 p.m.
NEDg	Description generation	`batch_6a108a88dd5c8190ac1f024420860c32`	completed	May 22, 2026, 4:55 p.m.
NED2	Entity disambiguation (via description)	`batch_6a108b266a648190874a4e80f1df2bb8`	completed	May 22, 2026, 4:58 p.m.
PD	Predicate disambiguation	`batch_69f4683b34748190818428489a226124`	completed	May 1, 2026, 8:45 a.m.

Created at: April 21, 2026, 2:10 p.m.