Triple

T30282511
Position Surface form Disambiguated ID Type / Status
Subject The World of Null-A E770139 entity
Predicate mainCharacter P1183 FINISHED
Object Gilbert Gosseyn
Gilbert Gosseyn is the amnesiac, reality-bending protagonist of A. E. van Vogt’s classic science fiction novel "The World of Null-A," known for his multiple bodies and evolving non-Aristotelian abilities.
E1916275 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: Gilbert Gosseyn | Statement: [The World of Null-A, mainCharacter, Gilbert Gosseyn]
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: Gilbert Gosseyn
Triple: [The World of Null-A, mainCharacter, Gilbert Gosseyn]
Generated description
Gilbert Gosseyn is the amnesiac, reality-bending protagonist of A. E. van Vogt’s classic science fiction novel "The World of Null-A," known for his multiple bodies and evolving non-Aristotelian abilities.

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_69f224868fa8819099127eaf8855a28f completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68106a8ac8190ab775d61ae360c56 completed May 2, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27989b92288190b554cd99151acb69 completed June 9, 2026, 4:37 a.m.
NEDg Description generation batch_6a27a6d8685c819088e8900160bbfe73 completed June 9, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_6a27a76a4ce0819081de47aefcca8d5a completed June 9, 2026, 5:40 a.m.
Created at: April 29, 2026, 7:45 p.m.