Triple

T25251153
Position Surface form Disambiguated ID Type / Status
Subject northwestern Hungary E632743 entity
Predicate containsMotorway P139729 FINISHED
Object M15 motorway
The M15 motorway is a key Hungarian highway that connects the M1 motorway to the Slovak border near Rajka, serving as an important international transit route between Hungary and Slovakia.
E2067176 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: M15 motorway | Statement: [northwestern Hungary, containsMotorway, M15 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: M15 motorway
Triple: [northwestern Hungary, containsMotorway, M15 motorway]
Generated description
The M15 motorway is a key Hungarian highway that connects the M1 motorway to the Slovak border near Rajka, serving as an important international transit route between Hungary and Slovakia.

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_69e75a8fdd3881909ba0b05aa5da92a7 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f686150f908190ba57742775f07870 completed May 2, 2026, 11:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a366553fbb08190859d614572109a62 completed June 20, 2026, 10:03 a.m.
NEDg Description generation batch_6a36660841b8819086965e412110c25f completed June 20, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_6a3666c5937c8190a41f48157f47f8dc completed June 20, 2026, 10:09 a.m.
Created at: April 21, 2026, 1:11 p.m.