Triple

T27442575
Position Surface form Disambiguated ID Type / Status
Subject Myrna Adele Williams E690977 entity
Predicate notableWork P4 FINISHED
Object The Mask of Fu Manchu
The Mask of Fu Manchu is a 1932 pre-Code adventure-horror film featuring Boris Karloff as the villainous Dr. Fu Manchu and Myrna Loy in one of her early, exotic villain roles.
 E1771808 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: The Mask of Fu Manchu | Statement: [Myrna Adele Williams, notableWork, The Mask of Fu Manchu]
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: The Mask of Fu Manchu
Triple: [Myrna Adele Williams, notableWork, The Mask of Fu Manchu]
Generated description
The Mask of Fu Manchu is a 1932 pre-Code adventure-horror film featuring Boris Karloff as the villainous Dr. Fu Manchu and Myrna Loy in one of her early, exotic villain roles.

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_69ef5200fa0481908e28508d6e2c149e completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62d8f3abc819088b471db8c3ba3bd completed May 2, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b256f1e48190abbb9f28856bfab1 completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b32353248190ac509d73a9910602 completed May 24, 2026, 8:13 a.m.
NED2 Entity disambiguation (via description) batch_6a12b3c695a0819099113dba54710362 completed May 24, 2026, 8:16 a.m.
Created at: April 27, 2026, 12:45 p.m.