Triple
T9920070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geoffrey Beevers |
E185970
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Caroline John
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.
|
E830522
|
NE FINISHED |
How this triple was built (4 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, spouse, Caroline John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caroline John Context triple: [Geoffrey Beevers, spouse, Caroline John]
-
A.
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.
-
B.
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."
-
C.
Caroline Black
Caroline Black is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Black.
-
D.
Caroline Ross
Caroline Ross is a film editor known for her work on the science fiction movie "Starship Troopers."
-
E.
Caroline Fry
Caroline Fry was a 19th-century English Christian writer and moralist known for her religious essays and devotional works.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Caroline John Triple: [Geoffrey Beevers, spouse, Caroline John]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Caroline John Target entity description: 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.
-
A.
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.
-
B.
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."
-
C.
Caroline Black
Caroline Black is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Black.
-
D.
Caroline Ross
Caroline Ross is a film editor known for her work on the science fiction movie "Starship Troopers."
-
E.
Caroline Fry
Caroline Fry was a 19th-century English Christian writer and moralist known for her religious essays and devotional works.
- F. None of above. chosen
Provenance (5 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_69d228b8974c81909a603407ebe3df1f |
completed | April 5, 2026, 9:17 a.m. |
| NEDg | Description generation | batch_69d22990ef5881908b6a6100d7dcf6e6 |
completed | April 5, 2026, 9:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d22a0cb0808190a6119dc0268c50b9 |
completed | April 5, 2026, 9:23 a.m. |
Created at: March 30, 2026, 8:42 p.m.