Triple

T31194791
Position Surface form Disambiguated ID Type / Status
Subject Marisa Ramirez E795288 entity
Predicate hasActedIn P15620 FINISHED
Object All Souls Day: Dia de los Muertos
All Souls Day: Dia de los Muertos is a 2005 horror film that blends Mexican Day of the Dead traditions with supernatural terror in a small town plagued by vengeful spirits.
E1951073 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: All Souls Day: Dia de los Muertos | Statement: [Marisa Ramirez, hasActedIn, All Souls Day: Dia de los Muertos]
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: All Souls Day: Dia de los Muertos
Triple: [Marisa Ramirez, hasActedIn, All Souls Day: Dia de los Muertos]
Generated description
All Souls Day: Dia de los Muertos is a 2005 horror film that blends Mexican Day of the Dead traditions with supernatural terror in a small town plagued by vengeful spirits.

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_69f224d7a6a481908187c4362a8a525f completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69bbe12f48190b60052af284c1d27 completed May 3, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29591a77208190b67d2a8c5f161130 completed June 10, 2026, 12:31 p.m.
NEDg Description generation batch_6a295f49d9048190bddbefd68a0d3a29 completed June 10, 2026, 12:57 p.m.
NED2 Entity disambiguation (via description) batch_6a295fa1c9688190b5483526ef6959ae completed June 10, 2026, 12:59 p.m.
Created at: April 29, 2026, 9:09 p.m.