Triple

T16416722
Position Surface form Disambiguated ID Type / Status
Subject Dawn Olivieri E398706 entity
Predicate givenName P17 FINISHED
Object Dawn
Dawn is a feminine given name derived from the English word for daybreak, often symbolizing new beginnings and light.
E250040 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: Dawn | Statement: [Dawn Olivieri, givenName, Dawn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dawn
Context triple: [Dawn Olivieri, givenName, Dawn]
  • A. Dawn
    Dawn is a novel by Elie Wiesel that explores the moral and psychological struggles of a young Holocaust survivor involved in a Jewish underground movement in British-controlled Palestine.
  • B. Dawn
    Dawn was a NASA space probe that studied the protoplanet Vesta and the dwarf planet Ceres in the asteroid belt using ion propulsion.
  • C. Dawn
    "Dawn" is a lesser-known novel by American author Eleanor H. Porter, best known for writing "Pollyanna."
  • D. Dawn
    Dawn is a leading American dishwashing liquid brand known for its strong grease-cutting power and use in wildlife rescue efforts.
  • E. Dawn
    Dawn is a central character in the crime thriller film "Catch .44," around whom much of the movie’s tense, intersecting plot revolves.
  • 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: Dawn
Triple: [Dawn Olivieri, givenName, Dawn]
Generated description
Dawn is a feminine given name derived from the English word for daybreak, often symbolizing new beginnings and light.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dawn
Target entity description: Dawn is a feminine given name derived from the English word for daybreak, often symbolizing new beginnings and light.
  • A. Dawn chosen
    Dawn is a feminine given name commonly associated with the early morning time when light first appears in the sky.
  • B. Dawn
    Dawn is a leading American dishwashing liquid brand known for its strong grease-cutting power and use in wildlife rescue efforts.
  • C. Dawn
    Dawn is a science fiction novel by Octavia E. Butler that opens her Xenogenesis (Lilith’s Brood) trilogy, exploring themes of alien contact, genetic manipulation, and the future of humanity.
  • D. Dawn
    Dawn is a novel by Elie Wiesel that explores the moral and psychological struggles of a young Holocaust survivor involved in a Jewish underground movement in British-controlled Palestine.
  • E. Dawn
    Dawn is a central character in the crime thriller film "Catch .44," around whom much of the movie’s tense, intersecting plot revolves.
  • F. None of above.

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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32877ff248190886717d3329421a7 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c6ca1bc8190a6c4f675ec8e3a53 completed May 10, 2026, 8:06 a.m.
NEDg Description generation batch_6a003e3b113c819083e1abc512631e2b completed May 10, 2026, 8:13 a.m.
NED2 Entity disambiguation (via description) batch_6a003eb6aa748190b0c8866af405794a completed May 10, 2026, 8:15 a.m.
Created at: April 10, 2026, 5:09 a.m.