Triple

T36126281
Position Surface form Disambiguated ID Type / Status
Subject Walsingham E1044887 entity
Predicate hasNotableBearer P458 FINISHED
Object Tim Walsingham
Tim Walsingham is a person notable enough to be recognized as a distinguished bearer of the Walsingham surname.
E2171027 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: Tim Walsingham | Statement: [Walsingham, hasNotableBearer, Tim Walsingham]
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: Tim Walsingham
Triple: [Walsingham, hasNotableBearer, Tim Walsingham]
Generated description
Tim Walsingham is a person notable enough to be recognized as a distinguished bearer of the Walsingham surname.

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_69f76e356c908190abc6ca1e6a05b011 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b2f7679c8190b7894c32d915ac3a completed May 3, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38de1137fc81909cf8fc2be26ec152 completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a3906857e388190bb32efe8cf264dc1 completed June 22, 2026, 9:55 a.m.
NED2 Entity disambiguation (via description) batch_6a3906ff31a48190a015553fda15baf4 completed June 22, 2026, 9:57 a.m.
Created at: May 3, 2026, 4:08 p.m.