Triple

T30533633
Position Surface form Disambiguated ID Type / Status
Subject Monty Banks E777076 entity
Predicate directed P7373 FINISHED
Object Queen of Hearts (1936 film)
Queen of Hearts (1936 film) is a 1936 British comedy film best known for its lighthearted story and direction by Italian-born filmmaker Monty Banks.
E1919265 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: Queen of Hearts (1936 film) | Statement: [Monty Banks, directed, Queen of Hearts (1936 film)]
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: Queen of Hearts (1936 film)
Triple: [Monty Banks, directed, Queen of Hearts (1936 film)]
Generated description
Queen of Hearts (1936 film) is a 1936 British comedy film best known for its lighthearted story and direction by Italian-born filmmaker Monty Banks.

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_69f2249c11508190ae7e955755ccfb01 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6884eba208190ba177d06a1111541 completed May 2, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27be81f03c8190874293df30769b4e completed June 9, 2026, 7:19 a.m.
NEDg Description generation batch_6a27c0a62c508190b40eca87b6bef1a2 completed June 9, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_6a27c10324348190a44216514590a529 completed June 9, 2026, 7:30 a.m.
Created at: April 29, 2026, 8:18 p.m.