Triple

T24888272
Position Surface form Disambiguated ID Type / Status
Subject Central Malawi E622918 entity
Predicate containsCity P294 FINISHED
Object Ntcheu
Ntcheu is a town in southern Malawi that serves as the administrative and commercial center of Ntcheu District, known for its agricultural activities and position along the main road between Lilongwe and Blantyre.
E1660591 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: Ntcheu | Statement: [Central Malawi, containsCity, Ntcheu]
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: Ntcheu
Triple: [Central Malawi, containsCity, Ntcheu]
Generated description
Ntcheu is a town in southern Malawi that serves as the administrative and commercial center of Ntcheu District, known for its agricultural activities and position along the main road between Lilongwe and Blantyre.

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_69e2fac597708190a922bf39a49ec70a completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f423428cbc8190b5372295f60df30e completed May 1, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a104890911c819084806d77c9bfa0c1 completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a1049d7d4bc819081cf52476b0c0a1d completed May 22, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_6a104a50e59c81908e576aeb2cebc1c5 completed May 22, 2026, 12:21 p.m.
Created at: April 18, 2026, 5:25 a.m.