Triple
T9920080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geoffrey Beevers |
E185970
|
entity |
| Predicate | spouseName |
P13
|
FINISHED |
| Object | Caroline John |
E830522
|
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: Caroline John | Statement: [Geoffrey Beevers, spouseName, Caroline John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caroline John Context triple: [Geoffrey Beevers, spouseName, Caroline John]
-
A.
Caroline John
chosen
Caroline John was a British actress best known for playing the Third Doctor’s companion Liz Shaw in the classic science fiction television series Doctor Who.
-
B.
Caroline Pearson
Caroline Pearson was the wife of English postal reformer Rowland Hill, known primarily through her association with his pioneering work on the modern postal system.
-
C.
Caroline Graham
Caroline Graham is a British crime novelist best known for creating the Chief Inspector Barnaby books that inspired the television series "Midsomer Murders."
-
D.
Caroline Black
Caroline Black is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Black.
-
E.
Caroline Ross
Caroline Ross is a film editor known for her work on the science fiction movie "Starship Troopers."
- 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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb5699bc48190961e036d1131fef0 |
completed | April 2, 2026, 12:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d2e676c81909e4eed258ecdf053 |
completed | April 5, 2026, 10:45 a.m. |
Created at: March 30, 2026, 8:42 p.m.