Triple

T33400291
Position Surface form Disambiguated ID Type / Status
Subject Hoşap E855276 entity
Predicate locatedOnTransportRoute P2409 FINISHED
Object Van–Hakkari road
The Van–Hakkari road is a major highway in eastern Turkey that connects the city of Van with the mountainous Hakkari region near the borders with Iran and Iraq.
E2050817 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: Van–Hakkari road | Statement: [Hoşap, locatedOnTransportRoute, Van–Hakkari road]
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: Van–Hakkari road
Triple: [Hoşap, locatedOnTransportRoute, Van–Hakkari road]
Generated description
The Van–Hakkari road is a major highway in eastern Turkey that connects the city of Van with the mountainous Hakkari region near the borders with Iran and Iraq.

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_69f3496e3f1c8190bcecfa82aa9d17ff completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e41396848190b73aa31c92f13fe1 completed May 3, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a358149b174819089ee694622efbab1 completed June 19, 2026, 5:50 p.m.
NEDg Description generation batch_6a35820972dc81908d3854fd2eae1288 completed June 19, 2026, 5:53 p.m.
NED2 Entity disambiguation (via description) batch_6a35828addb4819094e945cfbf65b72a completed June 19, 2026, 5:55 p.m.
Created at: May 1, 2026, 1:35 a.m.