Triple

T28518600
Position Surface form Disambiguated ID Type / Status
Subject Gabrielle Deschain E721694 entity
Predicate appearsIn P795 FINISHED
Object The Dark Tower: The Gunslinger Born
The Dark Tower: The Gunslinger Born is a Marvel Comics limited series that adapts and expands Stephen King’s Dark Tower universe, focusing on the early life and adventures of Roland Deschain.
E1860096 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: The Dark Tower: The Gunslinger Born | Statement: [Gabrielle Deschain, appearsIn, The Dark Tower: The Gunslinger Born]
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: The Dark Tower: The Gunslinger Born
Triple: [Gabrielle Deschain, appearsIn, The Dark Tower: The Gunslinger Born]
Generated description
The Dark Tower: The Gunslinger Born is a Marvel Comics limited series that adapts and expands Stephen King’s Dark Tower universe, focusing on the early life and adventures of Roland Deschain.

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_69f01a5cbcc4819083fb4e723378713e completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f64fa087648190abaf756ae4e8375c completed May 2, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2588fab4a481909faba4d2dfaf1cff completed June 7, 2026, 3:06 p.m.
NEDg Description generation batch_6a258d4474448190844fdc2216ecbd29 completed June 7, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_6a25985cf75081909194c11833399d37 completed June 7, 2026, 4:12 p.m.
Created at: April 28, 2026, 3:19 a.m.