Triple

T27562247
Position Surface form Disambiguated ID Type / Status
Subject Bari Centrale railway station E695803 entity
Predicate operatedBy P86 FINISHED
Object Ferrovie del Sud Est
Ferrovie del Sud Est is an Italian railway company that operates regional train and bus services primarily in the Apulia region of southern Italy.
E1785757 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: Ferrovie del Sud Est | Statement: [Bari Centrale railway station, operatedBy, Ferrovie del Sud Est]
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: Ferrovie del Sud Est
Triple: [Bari Centrale railway station, operatedBy, Ferrovie del Sud Est]
Generated description
Ferrovie del Sud Est is an Italian railway company that operates regional train and bus services primarily in the Apulia region of southern Italy.

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_69ef5387e97c8190a9dab040d21cd048 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62fbaa3388190b23c631f5c39ef06 completed May 2, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e43f20488190bfe7a89ccd4824d8 completed May 24, 2026, 11:42 a.m.
NEDg Description generation batch_6a12e54c1fec819087a9dc797de8266f completed May 24, 2026, 11:47 a.m.
NED2 Entity disambiguation (via description) batch_6a12e5f464d48190897fc67a618755c8 completed May 24, 2026, 11:50 a.m.
Created at: April 27, 2026, 1:39 p.m.