Triple
T17822138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katharine Tennant |
E445011
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Tennant |
—
|
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: Tennant | Statement: [Katharine Tennant, familyName, Tennant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tennant Context triple: [Katharine Tennant, familyName, Tennant]
-
A.
Tennant
chosen
Tennant is a British surname borne by various notable figures in the arts, sciences, and public life.
-
B.
Troughton
Troughton is a British surname most notably associated with actor Patrick Troughton, who played the Second Doctor in the long-running television series Doctor Who.
-
C.
Alex Tennant
Alex Tennant is a fictional character on the television series "NCIS: Hawaiʻi," depicted as the teenage son of lead agent Jane Tennant.
-
D.
John Tennant
John Tennant is a member of the Tennant family, related to the noted Scottish industrial chemist and entrepreneur Charles Tennant.
-
E.
Thurlestone
Thurlestone is a coastal village in South Devon, England, known for its scenic beaches, distinctive rock arch, and popularity as a holiday destination.
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48911b660819097fc7ea94665a02a |
completed | April 19, 2026, 7:49 a.m. |
Created at: April 10, 2026, 10:15 a.m.