Triple

T6767488
Position Surface form Disambiguated ID Type / Status
Subject Christiana Wyly E154758 entity
Predicate givenName P17 FINISHED
Object Christiana
Christiana is a personal name used as a given name, notably borne by individuals such as Christiana Wyly.
 E618173 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: Christiana | Statement: [Christiana Wyly, givenName, Christiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Christiana
Context triple: [Christiana Wyly, givenName, Christiana]
  • A. Bernardine
    Bernardine is a 1957 musical comedy film starring Pat Boone in one of his early leading screen roles.
  • B. Clementina
    Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
  • C. Constance
    Constance is a feminine given name of Latin origin, historically associated with nobility and meaning steadfastness or constancy.
  • D. Constance
    Constance is a historic city on Lake Constance in present-day Germany, best known as the site of the early 15th-century Council of Constance that ended the Western Schism in the Catholic Church.
  • E. Saint Isabel
    Saint Isabel is a Christian saint traditionally associated with charity, humility, and service to the poor, venerated in various regions that bear her name.
  • 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: Christiana
Triple: [Christiana Wyly, givenName, Christiana]
Generated description
Christiana is a personal name used as a given name, notably borne by individuals such as Christiana Wyly.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Christiana
Target entity description: Christiana is a personal name used as a given name, notably borne by individuals such as Christiana Wyly.
  • A. Bernardine
    Bernardine is a 1957 musical comedy film starring Pat Boone in one of his early leading screen roles.
  • B. Clementina
    Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
  • C. Constance
    Constance is a feminine given name of Latin origin, historically associated with nobility and meaning steadfastness or constancy.
  • D. Constance
    Constance is a historic city on Lake Constance in present-day Germany, best known as the site of the early 15th-century Council of Constance that ended the Western Schism in the Catholic Church.
  • E. Saint Isabel
    Saint Isabel is a Christian saint traditionally associated with charity, humility, and service to the poor, venerated in various regions that bear her name.
  • 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_69c688109c1c8190added9a221292af0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d231b79c81908a4f7fa8f253706d completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712c150088190b7e827cb1e45f1df completed March 27, 2026, 11:29 p.m.
NEDg Description generation batch_69c713a60ba481908f23eec839816d23 completed March 27, 2026, 11:32 p.m.
NED2 Entity disambiguation (via description) batch_69c71466728c81909a24174a7938b43a completed March 27, 2026, 11:36 p.m.
Created at: March 27, 2026, 2:12 p.m.