Triple

T29819396
Position Surface form Disambiguated ID Type / Status
Subject Sam Witwer E757203 entity
Predicate characterPortrayed P1507 FINISHED
Object Galen Marek
Galen Marek, also known as Starkiller, is the powerful Force-sensitive apprentice of Darth Vader and the central protagonist of the Star Wars: The Force Unleashed video game series.
E1887122 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: Galen Marek | Statement: [Sam Witwer, characterPortrayed, Galen Marek]
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: Galen Marek
Triple: [Sam Witwer, characterPortrayed, Galen Marek]
Generated description
Galen Marek, also known as Starkiller, is the powerful Force-sensitive apprentice of Darth Vader and the central protagonist of the Star Wars: The Force Unleashed video game 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_69f2245701c88190ad42415a0956c4ed completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6756645d48190a1645d578759dccd completed May 2, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26e5f728048190b7fee27a73664035 completed June 8, 2026, 3:55 p.m.
NEDg Description generation batch_6a26e6a791bc8190a52d36decacde222 completed June 8, 2026, 3:58 p.m.
NED2 Entity disambiguation (via description) batch_6a26e7ff07bc8190b23d1a9793f5233b completed June 8, 2026, 4:04 p.m.
Created at: April 29, 2026, 5:28 p.m.