Triple

T38880
Position Surface form Disambiguated ID Type / Status
Subject Herbert E769 entity
Predicate hasCognate P2525 FINISHED
Object Haribert E14792 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: Haribert | Statement: [Herbert, hasCognate, Haribert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haribert
Context triple: [Herbert, hasCognate, Haribert]
  • A. Aribert chosen
    Aribert is a Germanic given name, historically borne by medieval nobles and clergy, derived from elements meaning "army" and "bright."
  • B. Baron Balinhard
    Baron Balinhard is a Scottish peerage title historically associated with the noble family of the Earls of Southesk.
  • C. Willem
    Willem is a given name, primarily used in Dutch-speaking regions, that corresponds to the English name William.
  • D. Prince Ferdinand of Brunswick
    Prince Ferdinand of Brunswick was an 18th-century Prussian field marshal renowned for leading Allied forces against the French in Western Germany during the Seven Years' War.
  • E. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ec1ef5481909daf99654dfa3f57 completed Feb. 28, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2aa40b9fc819092323d52f6ae489d completed Feb. 28, 2026, 8:41 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.