Triple

T36382046
Position Surface form Disambiguated ID Type / Status
Subject Port of Mombasa E896071 entity
Predicate governedBy P46 FINISHED
Object Kenya Ports Authority Act
The Kenya Ports Authority Act is the legislation that establishes and regulates the Kenya Ports Authority, defining its powers, functions, and governance over seaports in Kenya.
E2181137 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: Kenya Ports Authority Act | Statement: [Port of Mombasa, governedBy, Kenya Ports Authority Act]
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: Kenya Ports Authority Act
Triple: [Port of Mombasa, governedBy, Kenya Ports Authority Act]
Generated description
The Kenya Ports Authority Act is the legislation that establishes and regulates the Kenya Ports Authority, defining its powers, functions, and governance over seaports in Kenya.

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_69f76e51d358819092bbc5f119f49476 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bb1c829081909b7e985f5f15cf1e completed May 3, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39b4326be481909f06114471bd7cd1 completed June 22, 2026, 10:16 p.m.
NEDg Description generation batch_6a39b4b6c6bc8190a229f76395dbdec3 completed June 22, 2026, 10:18 p.m.
NED2 Entity disambiguation (via description) batch_6a39b55a34108190bf8140198ebc468c completed June 22, 2026, 10:21 p.m.
Created at: May 3, 2026, 4:10 p.m.