Triple

T37718134
Position Surface form Disambiguated ID Type / Status
Subject Savage Sword of Conan E939508 entity
Predicate artist P184 FINISHED
Object Alfredo Alcala
Alfredo Alcala was a Filipino comic book artist renowned for his highly detailed, atmospheric inking and illustration work on fantasy and sword-and-sorcery titles, particularly in American comics.
E2290268 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: Alfredo Alcala | Statement: [Savage Sword of Conan, artist, Alfredo Alcala]
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: Alfredo Alcala
Triple: [Savage Sword of Conan, artist, Alfredo Alcala]
Generated description
Alfredo Alcala was a Filipino comic book artist renowned for his highly detailed, atmospheric inking and illustration work on fantasy and sword-and-sorcery titles, particularly in American comics.

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_69f76edc208c8190bc8b9683f75e1024 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbae6ffce8819099c7553121b60e4b completed May 6, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5bb15744cc8190a0c5c7eedbe94582 completed July 18, 2026, 5:01 p.m.
NEDg Description generation batch_6a5bb1ea499c8190a3e5c29b14baec33 completed July 18, 2026, 5:03 p.m.
NED2 Entity disambiguation (via description) batch_6a5bb21ff0cc8190aa89eff1bd3396d0 completed July 18, 2026, 5:04 p.m.
Created at: May 3, 2026, 4:18 p.m.