Triple

T35801607
Position Surface form Disambiguated ID Type / Status
Subject European route E77 E1034991 entity
Predicate usesNationalRoad P183693 FINISHED
Object Lithuanian A5 road
The Lithuanian A5 road is a major highway in Lithuania that forms part of an important north–south transport corridor linking the country with Poland and the broader European road network.
E2161240 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: Lithuanian A5 road | Statement: [European route E77, usesNationalRoad, Lithuanian A5 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: Lithuanian A5 road
Triple: [European route E77, usesNationalRoad, Lithuanian A5 road]
Generated description
The Lithuanian A5 road is a major highway in Lithuania that forms part of an important north–south transport corridor linking the country with Poland and the broader European road network.

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_69f76e169bd081909f16cd8c9ee7870c completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a8d67d608190b0d51c170f2c1d2a completed May 3, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae1663e481909d7135c4392a3c7b completed June 22, 2026, 3:37 a.m.
NEDg Description generation batch_6a38aec1b6508190a3bc1151af839daa completed June 22, 2026, 3:40 a.m.
NED2 Entity disambiguation (via description) batch_6a38af52e8288190abf63800ab6ce010 completed June 22, 2026, 3:43 a.m.
Created at: May 3, 2026, 4:06 p.m.