Triple

T24210109
Position Surface form Disambiguated ID Type / Status
Subject Joseph Calleia E600513 entity
Predicate birthName P65 FINISHED
Object Giuseppe Maria Spurrin-Calleja
Giuseppe Maria Spurrin-Calleja is the birth name of Joseph Calleia, a Maltese-American actor and singer known for his character roles in Hollywood films of the 1930s and 1940s.
E1623393 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: Giuseppe Maria Spurrin-Calleja | Statement: [Joseph Calleia, birthName, Giuseppe Maria Spurrin-Calleja]
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: Giuseppe Maria Spurrin-Calleja
Triple: [Joseph Calleia, birthName, Giuseppe Maria Spurrin-Calleja]
Generated description
Giuseppe Maria Spurrin-Calleja is the birth name of Joseph Calleia, a Maltese-American actor and singer known for his character roles in Hollywood films of the 1930s and 1940s.

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_69e2953344c48190875730c7d52112a0 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f282020a5881909df47f766c3ee7af completed April 29, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd1bf7508190a5da559303575d60 completed May 22, 2026, 2:19 a.m.
NEDg Description generation batch_6a0fbdb2afb8819080b49191b6369ec5 completed May 22, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbe63971c81908ab3e446da49765d completed May 22, 2026, 2:24 a.m.
Created at: April 17, 2026, 11:54 p.m.