Triple

T38595150
Position Surface form Disambiguated ID Type / Status
Subject Mozambique rail network E934051 entity
Predicate hasLine P35 FINISHED
Object Beira–Machipanda line
The Beira–Machipanda line is a key railway route in Mozambique that connects the port city of Beira to the Zimbabwean border, serving as an important regional freight and transport corridor.
 E2276956 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: Beira–Machipanda line | Statement: [Mozambique rail network, hasLine, Beira–Machipanda line]
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: Beira–Machipanda line
Triple: [Mozambique rail network, hasLine, Beira–Machipanda line]
Generated description
The Beira–Machipanda line is a key railway route in Mozambique that connects the port city of Beira to the Zimbabwean border, serving as an important regional freight and transport corridor.

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_69f76ecc17688190b389b693a5927501 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd94092a88190a5863ff145ec6ad8 completed May 7, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41eaa230748190b011df5db0c12875 completed June 29, 2026, 3:46 a.m.
NEDg Description generation batch_6a41ebe8dcd881909001bd8d084e498a completed June 29, 2026, 3:52 a.m.
NED2 Entity disambiguation (via description) batch_6a41ed04b20c81908453356ba5af16ee completed June 29, 2026, 3:56 a.m.
Created at: May 3, 2026, 4:32 p.m.