Triple
T7469976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Nixon Cox |
E176476
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cox |
E84235
|
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: Cox | Statement: [Christopher Nixon Cox, familyName, Cox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cox Context triple: [Christopher Nixon Cox, familyName, Cox]
-
A.
Cox
chosen
Cox is a common English surname of British and Irish origin, borne by numerous notable figures across politics, law, entertainment, and sports.
-
B.
Paxson
Paxson is a small unincorporated community in Alaska known as a remote junction and stopping point for travelers in the state's interior.
-
C.
Cox Enterprises
Cox Enterprises is a major U.S. privately held media, communications, and automotive services conglomerate.
-
D.
Couper
Couper is a surname and variant spelling of Cooper, used by various individuals and families, particularly in English-speaking regions.
-
E.
Farris
Farris is a surname most notably associated with Christine King Farris, an American educator, author, and the elder sister of Martin Luther King Jr.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3f845e081908117783ff1e63e23 |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8347b36388190989d2bcbe3f747bf |
completed | March 28, 2026, 8:05 p.m. |
Created at: March 27, 2026, 3:41 p.m.