Triple

T27190609
Position Surface form Disambiguated ID Type / Status
Subject Crossroads (2001 TV series) E683463 entity
Predicate productionCompany P490 FINISHED
Object Carlton Productions
Carlton Productions was a British television production company known for creating and producing a range of drama and entertainment programs for UK broadcasters.
E1760348 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: Carlton Productions | Statement: [Crossroads (2001 TV series), productionCompany, Carlton 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: Carlton Productions
Triple: [Crossroads (2001 TV series), productionCompany, Carlton Productions]
Generated description
Carlton Productions was a British television production company known for creating and producing a range of drama and entertainment programs for UK broadcasters.

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_69eefad140408190b8586fdebcf9af46 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625abb50081908345dd4cff9fee49 completed May 2, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a125395e7008190b35cb5184307bd3d completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a12546f814881908c806a1805b7473d completed May 24, 2026, 1:29 a.m.
NED2 Entity disambiguation (via description) batch_6a125512eb608190b958f82af3475535 completed May 24, 2026, 1:32 a.m.
Created at: April 27, 2026, 9:32 a.m.