Triple

T1271945
Position Surface form Disambiguated ID Type / Status
Subject Bette Davis E15728 entity
Predicate notableWork P4 FINISHED
Object Jezebel
Jezebel is a 1938 American drama film starring Bette Davis as a headstrong Southern belle whose defiance leads to personal and social ruin.
 E144655 NE FINISHED

How this triple was built (4 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: Jezebel | Statement: [Bette Davis, notableWork, Jezebel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jezebel
Context triple: [Bette Davis, notableWork, Jezebel]
  • A. Jezebel
    Jezebel is a feminist-leaning online magazine and blog known for its sharp commentary on gender, culture, and media.
  • B. Jezebel
    Jezebel is a notorious Phoenician queen in the Hebrew Bible, remembered for promoting Baal worship in Israel and for her violent conflict with the prophet Elijah.
  • C. Delilah
    Delilah is a biblical figure best known for betraying Samson by discovering and revealing the secret of his strength.
  • D. Maria Magdalena Keverich
    Maria Magdalena Keverich was a German woman best known as the mother of the composer Ludwig van Beethoven.
  • E. Ofelia
    Ofelia is the imaginative young girl in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth," whose encounters with mythical creatures mirror the brutal realities of post–Civil War Spain.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Jezebel
Triple: [Bette Davis, notableWork, Jezebel]
Generated description
Jezebel is a 1938 American drama film starring Bette Davis as a headstrong Southern belle whose defiance leads to personal and social ruin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jezebel
Target entity description: Jezebel is a 1938 American drama film starring Bette Davis as a headstrong Southern belle whose defiance leads to personal and social ruin.
  • A. Jezebel
    Jezebel is a feminist-leaning online magazine and blog known for its sharp commentary on gender, culture, and media.
  • B. Jezebel
    Jezebel is a notorious Phoenician queen in the Hebrew Bible, remembered for promoting Baal worship in Israel and for her violent conflict with the prophet Elijah.
  • C. Delilah
    Delilah is a biblical figure best known for betraying Samson by discovering and revealing the secret of his strength.
  • D. Maria Magdalena Keverich
    Maria Magdalena Keverich was a German woman best known as the mother of the composer Ludwig van Beethoven.
  • E. Ofelia
    Ofelia is the imaginative young girl in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth," whose encounters with mythical creatures mirror the brutal realities of post–Civil War Spain.
  • F. None of above. chosen

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_69a4935a94308190bb92555b79032824 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4c06c033081909bc594157abaf5bb completed March 1, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac998e56488190ac3cf51563335e30 completed March 7, 2026, 9:33 p.m.
NEDg Description generation batch_69ac9a13e9548190ae1fbfeba3326cd5 completed March 7, 2026, 9:35 p.m.
NED2 Entity disambiguation (via description) batch_69ac9a96d4f081908e608a3f247bbfb2 completed March 7, 2026, 9:37 p.m.
Created at: March 1, 2026, 7:50 p.m.