Triple
T20852042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doug Clifford |
E513388
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Clifford |
—
|
NE NERFINISHED |
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: Clifford | Statement: [Doug Clifford, familyName, Clifford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clifford Context triple: [Doug Clifford, familyName, Clifford]
-
A.
Clifford
chosen
Clifford is an English surname historically associated with several notable figures in British politics, nobility, and public life.
-
B.
Clifford
Clifford is the young boy protagonist of the 1991 horror-comedy film "Critters 3."
-
C.
Clifford
Clifford is a small village in West Yorkshire, England, known for its historic character and proximity to the town of Boston Spa.
-
D.
Clifford
Clifford is the given name of American actor and Academy Award winner Cliff Robertson.
-
E.
Clifford
Clifford is a masculine given name of English origin, historically associated with various notable figures in fields such as politics, sports, and the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3a4df5c8190aa0e7684ad6fc9f2 |
completed | April 21, 2026, 12:24 a.m. |
Created at: April 16, 2026, 12:43 p.m.