Triple

T23672071
Position Surface form Disambiguated ID Type / Status
Subject South Africa–Lesotho border E584756 entity
Predicate hasBorderCrossing P4105 FINISHED
Object Peka Bridge border post
Peka Bridge border post is a land border crossing point between South Africa and Lesotho, serving as an official gateway for travelers and trade between the two countries.
E1597337 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: Peka Bridge border post | Statement: [South Africa–Lesotho border, hasBorderCrossing, Peka Bridge border post]
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: Peka Bridge border post
Triple: [South Africa–Lesotho border, hasBorderCrossing, Peka Bridge border post]
Generated description
Peka Bridge border post is a land border crossing point between South Africa and Lesotho, serving as an official gateway for travelers and trade between the two countries.

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_69e24901421881908c17a5293bdd4a8e completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b41002f881908cd744ed44b70f5d completed April 29, 2026, 7:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f45baa43481909630316237462247 completed May 21, 2026, 5:49 p.m.
NEDg Description generation batch_6a0f4763990081908e12d512d26d3004 completed May 21, 2026, 5:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f48043bb4819088b982d9cce3b962 completed May 21, 2026, 5:59 p.m.
Created at: April 17, 2026, 6:50 p.m.