Triple

T30423416
Position Surface form Disambiguated ID Type / Status
Subject I Am Cuba E773957 entity
Predicate screenwriter P2831 FINISHED
Object Enrique Pineda Barnet
Enrique Pineda Barnet was a Cuban film director and screenwriter best known for his influential work in Cuban cinema, including co-writing the landmark film "I Am Cuba."
E2166021 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: Enrique Pineda Barnet | Statement: [I Am Cuba, screenwriter, Enrique Pineda Barnet]
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: Enrique Pineda Barnet
Triple: [I Am Cuba, screenwriter, Enrique Pineda Barnet]
Generated description
Enrique Pineda Barnet was a Cuban film director and screenwriter best known for his influential work in Cuban cinema, including co-writing the landmark film "I Am Cuba."

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_69f22491ba248190b9a4776ca8e42d02 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68666988c81909c9d2bfb95bc0355 completed May 2, 2026, 11:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38cb70ea788190a694e7363c777a3c completed June 22, 2026, 5:43 a.m.
NEDg Description generation batch_6a38cc7429608190976416e7fa580c99 completed June 22, 2026, 5:47 a.m.
NED2 Entity disambiguation (via description) batch_6a38cd14a5f48190b924f3818ebdf8e7 completed June 22, 2026, 5:50 a.m.
Created at: April 29, 2026, 8:06 p.m.