Triple

T35260906
Position Surface form Disambiguated ID Type / Status
Subject Arena (Star Trek: The Original Series) E1018367 entity
Predicate basedOn P98 FINISHED
Object Arena (short story)
"Arena" is a 1944 science fiction short story by Fredric Brown, best known for its influential premise of a human forced into single combat with an alien to decide the fate of their species and for inspiring a classic Star Trek episode.
E2133790 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: Arena (short story) | Statement: [Arena (Star Trek: The Original Series), basedOn, Arena (short story)]
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: Arena (short story)
Triple: [Arena (Star Trek: The Original Series), basedOn, Arena (short story)]
Generated description
"Arena" is a 1944 science fiction short story by Fredric Brown, best known for its influential premise of a human forced into single combat with an alien to decide the fate of their species and for inspiring a classic Star Trek episode.

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_69f76de4be5c8190a51705c07612cac8 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78f6f99f8819083a6cde4e47f8e1d completed May 3, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a380fb430c481908632b28532481d4f completed June 21, 2026, 4:22 p.m.
NEDg Description generation batch_6a38103c0bd881909b0e95da1efa3da9 completed June 21, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_6a3810c0f4708190ae5ac288af246fcd completed June 21, 2026, 4:26 p.m.
Created at: May 3, 2026, 4:02 p.m.