Triple

T25905228
Position Surface form Disambiguated ID Type / Status
Subject The Navigator E652732 entity
Predicate featuresCharacter P626 FINISHED
Object Betsy O’Brien
Betsy O’Brien is a central character in Eoin McNamee’s novel *The Navigator*, part of a fantasy series involving time manipulation and a battle against a mysterious force called the Harsh.
E1855154 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: Betsy O’Brien | Statement: [The Navigator, featuresCharacter, Betsy O’Brien]
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: Betsy O’Brien
Triple: [The Navigator, featuresCharacter, Betsy O’Brien]
Generated description
Betsy O’Brien is a central character in Eoin McNamee’s novel *The Navigator*, part of a fantasy series involving time manipulation and a battle against a mysterious force called the Harsh.

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_69e7ab3d3f8481909bc53ed64c06af33 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f603beb5248190aed52bf4e44f223c completed May 2, 2026, 2:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a256988a21481908682d6b61b8e98d0 completed June 7, 2026, 12:52 p.m.
NEDg Description generation batch_6a256f31adfc8190b5c86993112f300a completed June 7, 2026, 1:16 p.m.
NED2 Entity disambiguation (via description) batch_6a256f98942081909d86856ade8b24be completed June 7, 2026, 1:18 p.m.
Created at: April 22, 2026, 8:27 a.m.