Triple
T10776278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Dent |
E254204
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Dent |
E254204
|
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: Dent | Statement: [Richard Dent, hasSurname, Dent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dent Context triple: [Richard Dent, hasSurname, Dent]
-
A.
Dent
chosen
Dent is a surname most prominently associated with Richard Dent, a Hall of Fame former NFL defensive end for the Chicago Bears.
-
B.
Zahn
Zahn is a surname most prominently associated with American actor and comedian Steve Zahn, known for his roles in films like "That Thing You Do!" and "Saving Silverman."
-
C.
Muldental
Muldental is the valley region surrounding the Mulde River in Germany, known for its scenic landscapes and small towns.
-
D.
Zahniser
Zahniser is a surname most notably associated with Howard Zahniser, the American environmentalist and principal author of the U.S. Wilderness Act.
-
E.
Demon Dentist
"Demon Dentist" is a children's horror-comedy novel by David Walliams about a sinister new dentist whose terrifying secrets unsettle a young boy and his town.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7329d8c908190bddad40685133ea1 |
completed | April 9, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de238ff88881908676d38dca041cb4 |
completed | April 14, 2026, 11:22 a.m. |
Created at: April 8, 2026, 9:16 p.m.