Triple

T157985
Position Surface form Disambiguated ID Type / Status
Subject Writings E3219 entity
Predicate containsBook P5478 FINISHED
Object Esther
Esther is a book of the Hebrew Bible and Christian Old Testament that tells the story of a Jewish woman who becomes queen of Persia and courageously saves her people from annihilation.
 E20171 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: Esther | Statement: [Writings, containsBook, Esther]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Esther
Context triple: [Writings, containsBook, Esther]
  • A. Judith
    Judith is a deuterocanonical book of the Bible that tells the story of a courageous Jewish widow who saves her people by beheading the Assyrian general Holofernes.
  • B. Ruth
    Ruth is the given name of Ruth Bader Ginsburg, the pioneering U.S. Supreme Court Justice and prominent advocate for gender equality and civil rights.
  • C. Ruth
    Ruth is a book of the Hebrew Bible/Old Testament that tells the story of a Moabite woman whose loyalty and faith lead to her becoming an ancestor of King David.
  • D. Miryam
    Miryam is the Hebrew form of the name of the Virgin Mary, the mother of Jesus in Christian tradition.
  • E. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • 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: Esther
Triple: [Writings, containsBook, Esther]
Generated description
Esther is a book of the Hebrew Bible and Christian Old Testament that tells the story of a Jewish woman who becomes queen of Persia and courageously saves her people from annihilation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Esther
Target entity description: Esther is a book of the Hebrew Bible and Christian Old Testament that tells the story of a Jewish woman who becomes queen of Persia and courageously saves her people from annihilation.
  • A. Judith
    Judith is a deuterocanonical book of the Bible that tells the story of a courageous Jewish widow who saves her people by beheading the Assyrian general Holofernes.
  • B. Ruth
    Ruth is the given name of Ruth Bader Ginsburg, the pioneering U.S. Supreme Court Justice and prominent advocate for gender equality and civil rights.
  • C. Ruth
    Ruth is a book of the Hebrew Bible/Old Testament that tells the story of a Moabite woman whose loyalty and faith lead to her becoming an ancestor of King David.
  • D. Miryam
    Miryam is the Hebrew form of the name of the Virgin Mary, the mother of Jesus in Christian tradition.
  • E. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • 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_69a2527757ec819090b8becb2cf1a862 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a25bac998c819099f2bed899220a78 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2d732c32881909640c1c7be70e09a completed Feb. 28, 2026, 11:53 a.m.
NEDg Description generation batch_69a2d81b278081909d1c4e152cd2ef2c completed Feb. 28, 2026, 11:57 a.m.
NED2 Entity disambiguation (via description) batch_69a2d907b3fc8190bb63024feab379f1 completed Feb. 28, 2026, 12:01 p.m.
Created at: Feb. 28, 2026, 2:31 a.m.