Triple

T23452624
Position Surface form Disambiguated ID Type / Status
Subject A29 motorway E567824 entity
Predicate hasNameInItalian P17612 FINISHED
Object Autostrada A29
Autostrada A29 is a major Italian motorway in Sicily that connects Palermo with the island’s western and southwestern regions, including Trapani and Mazara del Vallo.
E2212975 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: Autostrada A29 | Statement: [A29 motorway, hasNameInItalian, Autostrada A29]
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: Autostrada A29
Triple: [A29 motorway, hasNameInItalian, Autostrada A29]
Generated description
Autostrada A29 is a major Italian motorway in Sicily that connects Palermo with the island’s western and southwestern regions, including Trapani and Mazara del Vallo.

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_69e2458b4c888190b1d7998f9862a558 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a64ded5c8190bd50ac5b9bbb0f5f completed April 29, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3efd90469c8190809aa78d37c14bd1 completed June 26, 2026, 10:30 p.m.
NEDg Description generation batch_6a3f4145d5788190a294d76bb2c620c6 completed June 27, 2026, 3:19 a.m.
NED2 Entity disambiguation (via description) batch_6a3f41b2c7f88190a83ee8645c165de4 completed June 27, 2026, 3:21 a.m.
Created at: April 17, 2026, 5:52 p.m.