Triple

T34377795
Position Surface form Disambiguated ID Type / Status
Subject John Bromfield E882339 entity
Predicate givenName P17 FINISHED
Object John
John is a masculine given name of Hebrew origin, commonly used in English-speaking countries and borne by numerous notable historical and contemporary figures.
E55602 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: John | Statement: [John Bromfield, givenName, John]
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: John
Triple: [John Bromfield, givenName, John]
Generated description
John is a masculine given name of Hebrew origin, commonly used in English-speaking countries and borne by numerous notable historical and contemporary figures.

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_69f349bf5d7481908dd5da4cbdf74047 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f718557a048190ba83c78e00445eae completed May 3, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a370db50c78819091d9d0219e17c0a3 completed June 20, 2026, 10:01 p.m.
NEDg Description generation batch_6a370e995d04819093fe5032b18243ad completed June 20, 2026, 10:05 p.m.
NED2 Entity disambiguation (via description) batch_6a370f63e1d08190a3e588bc7b2fa789 completed June 20, 2026, 10:08 p.m.
Created at: May 1, 2026, 1:59 a.m.