Triple

T34969279
Position Surface form Disambiguated ID Type / Status
Subject Flesh and Blood E1008488 entity
Predicate featuresCharacter P626 FINISHED
Object Tuvok
Tuvok is a Vulcan Starfleet officer and chief of security aboard the USS Voyager in the television series Star Trek: Voyager.
E308617 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: Tuvok | Statement: [Flesh and Blood, featuresCharacter, Tuvok]
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: Tuvok
Triple: [Flesh and Blood, featuresCharacter, Tuvok]
Generated description
Tuvok is a Vulcan Starfleet officer and chief of security aboard the USS Voyager in the television series Star Trek: Voyager.

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_69f76dc78a308190a1ac29ad4a9a4895 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78460a2e881908064c72b49d56bba completed May 3, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38dde459408190b102185449d10a35 completed June 22, 2026, 7:01 a.m.
NEDg Description generation batch_6a38f3daf5188190921d7e7cf19fd18a completed June 22, 2026, 8:35 a.m.
NED2 Entity disambiguation (via description) batch_6a38f513d3e88190aa25e33d93bf12a4 completed June 22, 2026, 8:40 a.m.
Created at: May 3, 2026, 4 p.m.