Triple
T9204683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Vokes |
E220940
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Christopher |
E220717
|
NE FINISHED |
How this triple was built (2 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: Christopher | Statement: [Christopher Vokes, givenName, Christopher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christopher Context triple: [Christopher Vokes, givenName, Christopher]
-
A.
Christopher
chosen
Christopher is a common masculine given name of Greek origin, meaning "bearer of Christ."
-
B.
Christopher
Christopher is a character in James Baldwin’s novel "Tell Me How Long the Train’s Been Gone," contributing to the book’s exploration of race, identity, and personal relationships in mid-20th-century America.
-
C.
Christopher
Christopher is the given first name of W. C. Handy, the influential American composer and musician often called the "Father of the Blues."
-
D.
Christopher
"Christopher" is a novel by British author Richard Pryce, best known as one of his more prominent works in late 19th-century fiction.
-
E.
Christopher
Christopher is the given first name of Chris Gardner, the American entrepreneur and motivational speaker whose life story inspired the film "The Pursuit of Happyness."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca83e8e9248190862cf3e41693b310 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd945f37881909f0d30eeb6a7a3ad |
completed | April 1, 2026, 8:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c4e56208190a5b2749b81e467be |
completed | April 4, 2026, 12:33 a.m. |
Created at: March 30, 2026, 7:26 p.m.