Triple

T35622277
Position Surface form Disambiguated ID Type / Status
Subject The Big Land (1957 film) E1029346 entity
Predicate productionCompany P490 FINISHED
Object Jaguar Productions
Jaguar Productions was a mid-20th-century American film production company associated with feature films such as the 1957 Western drama "The Big Land."
E2147436 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: Jaguar Productions | Statement: [The Big Land (1957 film), productionCompany, Jaguar Productions]
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: Jaguar Productions
Triple: [The Big Land (1957 film), productionCompany, Jaguar Productions]
Generated description
Jaguar Productions was a mid-20th-century American film production company associated with feature films such as the 1957 Western drama "The Big Land."

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_69f76e0709408190bbe322bf1707ef6b completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79ef2a6a08190a1722891792b7737 completed May 3, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a385bf555108190b41ad530941c42ee completed June 21, 2026, 9:47 p.m.
NEDg Description generation batch_6a385d4a1b9c81908f8eaca4b6fb952e completed June 21, 2026, 9:53 p.m.
NED2 Entity disambiguation (via description) batch_6a385dd6f1808190ab7f9530743cf1d6 completed June 21, 2026, 9:55 p.m.
Created at: May 3, 2026, 4:05 p.m.