Triple

T5487814
Position Surface form Disambiguated ID Type / Status
Subject Andrea Barrett E123626 entity
Predicate notableWork P4 FINISHED
Object Archangel
Archangel is a historical fiction collection by Andrea Barrett that intertwines science, war, and personal relationships in early 20th-century settings.
 E522818 NE FINISHED

How this triple was built (4 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: Archangel | Statement: [Andrea Barrett, notableWork, Archangel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Archangel
Context triple: [Andrea Barrett, notableWork, Archangel]
  • A. Archangel
    Archangel is a historic Russian port city on the White Sea that served as a major northern gateway for European trade before the rise of St. Petersburg.
  • B. El Ángel
    El Ángel is a famous victory column and iconic symbol of Mexico City commemorating the country’s independence.
  • C. Angelus
    The Angelus is a traditional Catholic prayer recited three times daily in honor of the Incarnation, often accompanied by the ringing of church bells.
  • D. Archangel City
    Archangel City is an alternative name for the Russian port city of Arkhangelsk, a historic hub of Arctic trade and shipbuilding on the White Sea.
  • E. Erskyne
    Erskyne is an alternative spelling or variant form of the name Erskine, which is used as a surname and given name of Scottish origin.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Archangel
Triple: [Andrea Barrett, notableWork, Archangel]
Generated description
Archangel is a historical fiction collection by Andrea Barrett that intertwines science, war, and personal relationships in early 20th-century settings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Archangel
Target entity description: Archangel is a historical fiction collection by Andrea Barrett that intertwines science, war, and personal relationships in early 20th-century settings.
  • A. Archangel
    Archangel is a historic Russian port city on the White Sea that served as a major northern gateway for European trade before the rise of St. Petersburg.
  • B. El Ángel
    El Ángel is a famous victory column and iconic symbol of Mexico City commemorating the country’s independence.
  • C. Angelus
    The Angelus is a traditional Catholic prayer recited three times daily in honor of the Incarnation, often accompanied by the ringing of church bells.
  • D. Archangel City
    Archangel City is an alternative name for the Russian port city of Arkhangelsk, a historic hub of Arctic trade and shipbuilding on the White Sea.
  • E. Erskyne
    Erskyne is an alternative spelling or variant form of the name Erskine, which is used as a surname and given name of Scottish origin.
  • F. None of above. chosen

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_69bd464a2d908190869324ce176779c8 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd9264d014819097c83bb5c2bb8c39 completed March 20, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf48aa12708190add69c5fd51d161d completed March 22, 2026, 1:40 a.m.
NEDg Description generation batch_69bf4a2b6c508190ad13f6d9823ad747 completed March 22, 2026, 1:47 a.m.
NED2 Entity disambiguation (via description) batch_69bf4a87d1fc8190a0e0e75d6f9cd766 completed March 22, 2026, 1:48 a.m.
Created at: March 20, 2026, 2:10 p.m.