Triple

T15900164
Position Surface form Disambiguated ID Type / Status
Subject Kwekwe E385563 entity
Predicate locatedOn P40 FINISHED
Object A5 highway
The A5 highway is a major road in Zimbabwe that connects the cities of Harare and Bulawayo, passing through Kwekwe and other central towns.
E1719911 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: A5 highway | Statement: [Kwekwe, locatedOn, A5 highway]
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: A5 highway
Triple: [Kwekwe, locatedOn, A5 highway]
Generated description
The A5 highway is a major road in Zimbabwe that connects the cities of Harare and Bulawayo, passing through Kwekwe and other central towns.

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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563cd2f081909404d724ecc8785a completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a119a1126648190b02638a1ac43216a completed May 23, 2026, 12:14 p.m.
NEDg Description generation batch_6a119ad502f4819094bacc5b50514200 completed May 23, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_6a119b5af6f48190a607628edf5bd0c8 completed May 23, 2026, 12:19 p.m.
Created at: April 10, 2026, 4:51 a.m.