Triple

T26470214
Position Surface form Disambiguated ID Type / Status
Subject Amelia Edwards E665878 entity
Predicate notableWork P4 FINISHED
Object A Thousand Miles up the Nile
A Thousand Miles up the Nile is a 19th-century travel narrative by Amelia Edwards that recounts her journey through Egypt and helped spark widespread Western interest in Egyptian archaeology.
 E1725545 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: A Thousand Miles up the Nile | Statement: [Amelia Edwards, notableWork, A Thousand Miles up the Nile]
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: A Thousand Miles up the Nile
Triple: [Amelia Edwards, notableWork, A Thousand Miles up the Nile]
Generated description
A Thousand Miles up the Nile is a 19th-century travel narrative by Amelia Edwards that recounts her journey through Egypt and helped spark widespread Western interest in Egyptian archaeology.

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_69ee883f80dc819090e311b022b78e02 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f612c7e55c81909443bc7130d927a4 completed May 2, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aee1665081908c35073e6532903a completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11b01df9348190a991161aa1fb8018 completed May 23, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_6a11b1230c148190931c49c9df40caa4 completed May 23, 2026, 1:52 p.m.
Created at: April 27, 2026, 12:19 a.m.