Triple

T24627757
Position Surface form Disambiguated ID Type / Status
Subject Nimrod E609588 entity
Predicate carriedPerson P24081 FINISHED
Object Bernard Day
Bernard Day was an early 20th-century Antarctic explorer and mechanic who participated in Ernest Shackleton’s Nimrod Expedition.
E1643838 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: Bernard Day | Statement: [Nimrod, carriedPerson, Bernard Day]
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: Bernard Day
Triple: [Nimrod, carriedPerson, Bernard Day]
Generated description
Bernard Day was an early 20th-century Antarctic explorer and mechanic who participated in Ernest Shackleton’s Nimrod Expedition.

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_69e2c4d1d3708190a0f2dc6a3a8523bb completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f2aab750888190b5ef44e77be2e633 completed April 30, 2026, 1:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10048727308190920dc00cb4ff9711 completed May 22, 2026, 7:23 a.m.
NEDg Description generation batch_6a100640e64081909c54d3a2761007fb completed May 22, 2026, 7:31 a.m.
NED2 Entity disambiguation (via description) batch_6a1006c065cc81908af8ae63739b4c37 completed May 22, 2026, 7:33 a.m.
Created at: April 18, 2026, 2:32 a.m.