Triple

T32963371
Position Surface form Disambiguated ID Type / Status
Subject Kimberley, Northern Cape E843300 entity
Predicate hasLandmark P105 FINISHED
Object Honoured Dead Memorial
The Honoured Dead Memorial is a prominent war monument in Kimberley, South Africa, commemorating those who died during the Siege of Kimberley in the Second Boer War.
 E2032010 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: Honoured Dead Memorial | Statement: [Kimberley, Northern Cape, hasLandmark, Honoured Dead Memorial]
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: Honoured Dead Memorial
Triple: [Kimberley, Northern Cape, hasLandmark, Honoured Dead Memorial]
Generated description
The Honoured Dead Memorial is a prominent war monument in Kimberley, South Africa, commemorating those who died during the Siege of Kimberley in the Second Boer War.

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_69f3494af2808190ad98cec2f1bc0fe6 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d17c712481909167630ecab98f43 completed May 3, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34dab9b50c81908eab5e3d23d12ecc completed June 19, 2026, 5:59 a.m.
NEDg Description generation batch_6a34db753bb481908fc733bcb6435ce0 completed June 19, 2026, 6:02 a.m.
NED2 Entity disambiguation (via description) batch_6a34dc2878848190b39175fdefeeeb18 completed June 19, 2026, 6:05 a.m.
Created at: May 1, 2026, 1:21 a.m.