Triple

T21284194
Position Surface form Disambiguated ID Type / Status
Subject Maputo Province E524609 entity
Predicate hasMunicipality P847 FINISHED
Object Manhiça
Manhiça is a town and district in southern Mozambique known for its agricultural activities and for hosting the prominent Manhiça Health Research Centre.
E1476075 NE FINISHED

How this triple was built (4 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: Manhiça | Statement: [Maputo Province, hasMunicipality, Manhiça]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manhiça
Context triple: [Maputo Province, hasMunicipality, Manhiça]
  • A. Manchita
    Manchita is a small municipality in the province of Badajoz, within Spain’s autonomous community of Extremadura.
  • B. Manhoy
    Manhoy is a barangay (village-level administrative division) of the municipality of Dumalag in the province of Capiz, Philippines.
  • C. Manide
    Manide is an endangered Austronesian language spoken by the Manide (Negrito) people in parts of southern Luzon in the Philippines.
  • D. Kamanje
    Kamanje is a small village and municipality located in Karlovac County in central Croatia, near the Slovenian border.
  • E. Manganiyar
    The Manganiyar are a hereditary community of Muslim folk musicians from Rajasthan and Sindh, renowned for their rich oral tradition, devotional and celebratory songs, and distinctive use of instruments like the kamaicha and dholak.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Manhiça
Triple: [Maputo Province, hasMunicipality, Manhiça]
Generated description
Manhiça is a town and district in southern Mozambique known for its agricultural activities and for hosting the prominent Manhiça Health Research Centre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Manhiça
Target entity description: Manhiça is a town and district in southern Mozambique known for its agricultural activities and for hosting the prominent Manhiça Health Research Centre.
  • A. Manchita
    Manchita is a small municipality in the province of Badajoz, within Spain’s autonomous community of Extremadura.
  • B. Manhoy
    Manhoy is a barangay (village-level administrative division) of the municipality of Dumalag in the province of Capiz, Philippines.
  • C. Manide
    Manide is an endangered Austronesian language spoken by the Manide (Negrito) people in parts of southern Luzon in the Philippines.
  • D. Kamanje
    Kamanje is a small village and municipality located in Karlovac County in central Croatia, near the Slovenian border.
  • E. Manganiyar
    The Manganiyar are a hereditary community of Muslim folk musicians from Rajasthan and Sindh, renowned for their rich oral tradition, devotional and celebratory songs, and distinctive use of instruments like the kamaicha and dholak.
  • F. None of above. chosen

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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d4e7f881909c2cc7936a66b79d completed April 21, 2026, 8:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09980794088190a54f7f00c2d3b3fb completed May 17, 2026, 10:27 a.m.
NEDg Description generation batch_6a0998a3326481908a4dfddfb7b2ecd9 completed May 17, 2026, 10:29 a.m.
NED2 Entity disambiguation (via description) batch_6a09996c8d7c81908cc9874f6e1a3fff completed May 17, 2026, 10:33 a.m.
Created at: April 16, 2026, 4:03 p.m.