Triple

T25576773
Position Surface form Disambiguated ID Type / Status
Subject Star Trek: The Lost Era E641126 entity
Predicate hasVolume P1567 FINISHED
Object Catalyst of Sorrows
Catalyst of Sorrows is a Star Trek: The Lost Era novel set in the franchise’s historical gap years, exploring political and character-driven events that shape the Star Trek universe between the established television series.
 E1688108 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: Catalyst of Sorrows | Statement: [Star Trek: The Lost Era, hasVolume, Catalyst of Sorrows]
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: Catalyst of Sorrows
Triple: [Star Trek: The Lost Era, hasVolume, Catalyst of Sorrows]
Generated description
Catalyst of Sorrows is a Star Trek: The Lost Era novel set in the franchise’s historical gap years, exploring political and character-driven events that shape the Star Trek universe between the established television series.

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_69e75dc281bc819095ec04dc0c3a94d0 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f9306d408190b05bc82de8ecfb84 completed May 2, 2026, 1:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b75f45708190bcc0277f4c1f4526 completed May 22, 2026, 8:06 p.m.
NEDg Description generation batch_6a10b9966114819093e81a647905346a completed May 22, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a10ba344df081908266aaa1920d9f3d completed May 22, 2026, 8:19 p.m.
Created at: April 21, 2026, 4:01 p.m.