Triple

T32931759
Position Surface form Disambiguated ID Type / Status
Subject Charlotte Byron Symonds E842416 entity
Predicate relative P37 FINISHED
Object Harriet Sykes Symonds
Harriet Sykes Symonds was a member of the Symonds family connected to Charlotte Byron Symonds, likely part of a 19th-century British intellectual or professional milieu.
E2029704 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: Harriet Sykes Symonds | Statement: [Charlotte Byron Symonds, relative, Harriet Sykes Symonds]
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: Harriet Sykes Symonds
Triple: [Charlotte Byron Symonds, relative, Harriet Sykes Symonds]
Generated description
Harriet Sykes Symonds was a member of the Symonds family connected to Charlotte Byron Symonds, likely part of a 19th-century British intellectual or professional milieu.

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_69f34948adfc8190a937f1f622783c0b completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d10602d4819099a5c334047ff1bd completed May 3, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34d2642be88190b3834d23da8cd900 completed June 19, 2026, 5:23 a.m.
NEDg Description generation batch_6a34d32a229481909a407bea93892806 completed June 19, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_6a34d3ab5e98819091f34300bf83621d completed June 19, 2026, 5:29 a.m.
Created at: May 1, 2026, 1:20 a.m.