Triple

T33313299
Position Surface form Disambiguated ID Type / Status
Subject Via Carpatia E852943 entity
Predicate followsRoad P20522 FINISHED
Object Hungarian M4 motorway
The Hungarian M4 motorway is a major east–west highway in Hungary that forms part of the international Via Carpatia corridor, improving connectivity between Central and Eastern Europe.
E2048277 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: Hungarian M4 motorway | Statement: [Via Carpatia, followsRoad, Hungarian M4 motorway]
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: Hungarian M4 motorway
Triple: [Via Carpatia, followsRoad, Hungarian M4 motorway]
Generated description
The Hungarian M4 motorway is a major east–west highway in Hungary that forms part of the international Via Carpatia corridor, improving connectivity between Central and Eastern Europe.

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_69f349679fd8819093b9b40e989440e3 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6decdd1188190ac601c1fcbcd31d6 completed May 3, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3551faa46081908d212f747f408c1e completed June 19, 2026, 2:28 p.m.
NEDg Description generation batch_6a355cf1e0b48190b057cce6b0c99022 completed June 19, 2026, 3:14 p.m.
NED2 Entity disambiguation (via description) batch_6a355eb730048190b44ec9de60626c0f completed June 19, 2026, 3:22 p.m.
Created at: May 1, 2026, 1:33 a.m.