Triple

T33232124
Position Surface form Disambiguated ID Type / Status
Subject The Pirates of Zan E850722 entity
Predicate hasMainCharacter P1183 FINISHED
Object Bron Hoddan
Bron Hoddan is the resourceful, technically skilled protagonist of Murray Leinster’s science fiction novel "The Pirates of Zan," known for blending engineering ingenuity with swashbuckling space adventure.
E2041244 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: Bron Hoddan | Statement: [The Pirates of Zan, hasMainCharacter, Bron Hoddan]
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: Bron Hoddan
Triple: [The Pirates of Zan, hasMainCharacter, Bron Hoddan]
Generated description
Bron Hoddan is the resourceful, technically skilled protagonist of Murray Leinster’s science fiction novel "The Pirates of Zan," known for blending engineering ingenuity with swashbuckling space adventure.

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_69f349613f988190a1eb75467d167122 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6daae0f3481908a8c90bd033948b1 completed May 3, 2026, 5:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a352fdc8c148190842489e10e5f1076 completed June 19, 2026, 12:02 p.m.
NEDg Description generation batch_6a3530dd26188190990588834837e034 completed June 19, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_6a3531f1f7b8819095b3ebb58ff09aa7 completed June 19, 2026, 12:11 p.m.
Created at: May 1, 2026, 1:30 a.m.