Triple

T34864527
Position Surface form Disambiguated ID Type / Status
Subject Lviv–Przemyśl railway E1004975 entity
Predicate partOf P40 FINISHED
Object Polish–Ukrainian rail network
The Polish–Ukrainian rail network is the system of cross-border railway lines and connections linking Poland and Ukraine, facilitating international passenger and freight transport between the two countries.
E2114857 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: Polish–Ukrainian rail network | Statement: [Lviv–Przemyśl railway, partOf, Polish–Ukrainian rail network]
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: Polish–Ukrainian rail network
Triple: [Lviv–Przemyśl railway, partOf, Polish–Ukrainian rail network]
Generated description
The Polish–Ukrainian rail network is the system of cross-border railway lines and connections linking Poland and Ukraine, facilitating international passenger and freight transport between the two countries.

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_69f76dbb678081909a247b9b5e1a73ac completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7817fb7808190879df16fbdac5809 completed May 3, 2026, 5:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a377960d32481908ec5f3b85d1a5425 completed June 21, 2026, 5:40 a.m.
NEDg Description generation batch_6a377a02724c8190a2ea67c5b5831aea completed June 21, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_6a377ac60cd88190b1ea9540346df1c9 completed June 21, 2026, 5:46 a.m.
Created at: May 3, 2026, 4 p.m.