Triple

T27791856
Position Surface form Disambiguated ID Type / Status
Subject Tema Metropolitan District E701100 entity
Predicate borderedBy P224 FINISHED
Object Kpone-Katamanso Municipal District
Kpone-Katamanso Municipal District is a local government administrative area in the Greater Accra Region of Ghana, known for its rapidly growing urban and industrial zones.
E1789655 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: Kpone-Katamanso Municipal District | Statement: [Tema Metropolitan District, borderedBy, Kpone-Katamanso Municipal District]
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: Kpone-Katamanso Municipal District
Triple: [Tema Metropolitan District, borderedBy, Kpone-Katamanso Municipal District]
Generated description
Kpone-Katamanso Municipal District is a local government administrative area in the Greater Accra Region of Ghana, known for its rapidly growing urban and industrial zones.

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_69ef6a50d8088190acbf3dfbb06d8091 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f63808280c8190aa654c05ebdeec0e completed May 2, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12eccc42608190bd45cec7b44fdbbe completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12ee3f436c8190b1daf7ec5041304e completed May 24, 2026, 12:25 p.m.
NED2 Entity disambiguation (via description) batch_6a12eef15e2c819099088626fb78adce completed May 24, 2026, 12:28 p.m.
Created at: April 27, 2026, 5:28 p.m.