Triple

T423647
Position Surface form Disambiguated ID Type / Status
Subject Emily Warren Roebling E8158 entity
Predicate givenName P17 FINISHED
Object Emily
Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
 E73544 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: Emily | Statement: [Emily Warren Roebling, givenName, Emily]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emily
Context triple: [Emily Warren Roebling, givenName, Emily]
  • A. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • B. Jane
    Jane is a feminine given name of English origin that has been widely used in many English-speaking countries for centuries.
  • C. Jennifer
    Jennifer is a common feminine given name of English origin, derived from the Cornish form of Guinevere and widely used in many English-speaking countries.
  • D. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • E. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • 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: Emily
Triple: [Emily Warren Roebling, givenName, Emily]
Generated description
Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emily
Target entity description: Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • A. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • B. Jane
    Jane is a feminine given name of English origin that has been widely used in many English-speaking countries for centuries.
  • C. Jennifer
    Jennifer is a common feminine given name of English origin, derived from the Cornish form of Guinevere and widely used in many English-speaking countries.
  • D. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • E. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • 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_69a2e7f1d1bc81909cf2dc9754a3c334 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2eed3e4cc8190ba6aff3bd1adb06f completed Feb. 28, 2026, 1:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5103417008190ab3755dbba5f7622 completed March 2, 2026, 4:21 a.m.
NEDg Description generation batch_69a510cee8808190b9fad02e85f96af1 completed March 2, 2026, 4:23 a.m.
NED2 Entity disambiguation (via description) batch_69a5113da3f881909abea82da8fb31d5 completed March 2, 2026, 4:25 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.