Triple

T34370193
Position Surface form Disambiguated ID Type / Status
Subject Luigia Lollobrigida E882129 entity
Predicate notableWork P4 FINISHED
Object Solomon and Sheba
"Solomon and Sheba" is a 1959 biblical epic film dramatizing the legendary romance and political intrigue between Israel’s King Solomon and the Queen of Sheba.
E2092756 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: Solomon and Sheba | Statement: [Luigia Lollobrigida, notableWork, Solomon and Sheba]
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: Solomon and Sheba
Triple: [Luigia Lollobrigida, notableWork, Solomon and Sheba]
Generated description
"Solomon and Sheba" is a 1959 biblical epic film dramatizing the legendary romance and political intrigue between Israel’s King Solomon and the Queen of Sheba.

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_69f349bf5d7481908dd5da4cbdf74047 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7184f93a48190b2524ed09be76f06 completed May 3, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3704ae23b881908d28cc58c0b8dd64 completed June 20, 2026, 9:22 p.m.
NEDg Description generation batch_6a3705a276b08190ad366c805fc6d4da completed June 20, 2026, 9:26 p.m.
NED2 Entity disambiguation (via description) batch_6a37061b69fc81908c02244b45d74771 completed June 20, 2026, 9:28 p.m.
Created at: May 1, 2026, 1:59 a.m.