Triple

T28319481
Position Surface form Disambiguated ID Type / Status
Subject Andras Hamori E717235 entity
Predicate notableWork P4 FINISHED
Object Sunshine
"Sunshine" is a Hungarian drama film produced by András Hámori that traces the multi-generational saga of a Jewish family through the political upheavals of 20th-century Central Europe.
E1222166 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: Sunshine | Statement: [Andras Hamori, notableWork, Sunshine]
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: Sunshine
Triple: [Andras Hamori, notableWork, Sunshine]
Generated description
"Sunshine" is a Hungarian drama film produced by András Hámori that traces the multi-generational saga of a Jewish family through the political upheavals of 20th-century Central Europe.

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_69eff6e6c3b08190ad78de6ba7f04548 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64928a6e081909ad15b53b17b7c3d completed May 2, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1632f2d2388190b949e000d8ecf5f5 completed May 26, 2026, 11:55 p.m.
NEDg Description generation batch_6a1633a0bd1881908757c68e04bdc509 completed May 26, 2026, 11:58 p.m.
NED2 Entity disambiguation (via description) batch_6a1634122f8c8190af25b6651fd12796 completed May 27, 2026, midnight
Created at: April 28, 2026, 12:23 a.m.