Triple

T32798627
Position Surface form Disambiguated ID Type / Status
Subject Terminal B (Tolmachevo Airport) E838836 entity
Predicate connectedTo P37 FINISHED
Object Terminal A (Tolmachevo Airport)
Terminal A at Tolmachevo Airport is one of the airport’s main passenger terminals, handling domestic flights and providing check-in, boarding, and arrival facilities.
E2023078 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: Terminal A (Tolmachevo Airport) | Statement: [Terminal B (Tolmachevo Airport), connectedTo, Terminal A (Tolmachevo Airport)]
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: Terminal A (Tolmachevo Airport)
Triple: [Terminal B (Tolmachevo Airport), connectedTo, Terminal A (Tolmachevo Airport)]
Generated description
Terminal A at Tolmachevo Airport is one of the airport’s main passenger terminals, handling domestic flights and providing check-in, boarding, and arrival facilities.

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_69f3493c7f6881908edf2aa13631d1e0 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cd7f8ff48190ad52bfd061b3616a completed May 3, 2026, 4:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b17085fc8190b52b6f9a6d792129 completed June 19, 2026, 3:03 a.m.
NEDg Description generation batch_6a34b29d06088190a46ae528f21056e9 completed June 19, 2026, 3:08 a.m.
NED2 Entity disambiguation (via description) batch_6a34b31c85108190a684cf1750b560f5 completed June 19, 2026, 3:10 a.m.
Created at: May 1, 2026, 1:14 a.m.