Triple

T31156221
Position Surface form Disambiguated ID Type / Status
Subject Riyadh–Qurayyat passenger line E794214 entity
Predicate hasStation P35 FINISHED
Object Hail railway station
Hail railway station is a passenger rail station in Ha'il, Saudi Arabia, serving as one of the stops on the Riyadh–Qurayyat railway line operated by Saudi Railways.
E1948782 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: Hail railway station | Statement: [Riyadh–Qurayyat passenger line, hasStation, Hail railway station]
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: Hail railway station
Triple: [Riyadh–Qurayyat passenger line, hasStation, Hail railway station]
Generated description
Hail railway station is a passenger rail station in Ha'il, Saudi Arabia, serving as one of the stops on the Riyadh–Qurayyat railway line operated by Saudi Railways.

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_69f224d504908190b01278dcb7fc3fa7 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f697f3d0e881909ec6c3e2cfbed20f completed May 3, 2026, 12:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2947269898819083742fb4afb173f1 completed June 10, 2026, 11:14 a.m.
NEDg Description generation batch_6a2947cb99048190b349aa52120b1e24 completed June 10, 2026, 11:17 a.m.
NED2 Entity disambiguation (via description) batch_6a2948b2f428819097e2d0fb35346b35 completed June 10, 2026, 11:21 a.m.
Created at: April 29, 2026, 9:07 p.m.