Triple

T32814933
Position Surface form Disambiguated ID Type / Status
Subject The Christmas Secret (2014) E839258 entity
Predicate productionCompany P490 FINISHED
Object Craig Anderson Productions
Craig Anderson Productions is a film and television production company known for creating made-for-TV movies such as the holiday drama "The Christmas Secret" (2014).
E2022397 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: Craig Anderson Productions | Statement: [The Christmas Secret (2014), productionCompany, Craig Anderson 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: Craig Anderson Productions
Triple: [The Christmas Secret (2014), productionCompany, Craig Anderson Productions]
Generated description
Craig Anderson Productions is a film and television production company known for creating made-for-TV movies such as the holiday drama "The Christmas Secret" (2014).

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_69f3493df9008190a8f5d843dcd77704 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cdce62d4819082dc7ea3214764e4 completed May 3, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b17e286c819085bcd7e122099f94 completed June 19, 2026, 3:03 a.m.
NEDg Description generation batch_6a34b20e8e9881909b3a425431f5a449 completed June 19, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a34b28efeac819080bec50507fcb9c4 completed June 19, 2026, 3:07 a.m.
Created at: May 1, 2026, 1:15 a.m.