Triple
T4881564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Moneypenny |
E109338
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Ian Fleming |
E3433
|
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: Ian Fleming | Statement: [Miss Moneypenny, createdBy, Ian Fleming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ian Fleming Context triple: [Miss Moneypenny, createdBy, Ian Fleming]
-
A.
Ian Fleming
chosen
Ian Fleming was a British author and journalist best known as the creator of the James Bond spy novels.
-
B.
John le Carré
John le Carré was a renowned British novelist best known for his sophisticated espionage thrillers that explored the moral ambiguities of Cold War intelligence work.
-
C.
William Fleming
William Fleming is a relatively common personal name shared by multiple notable individuals across fields such as politics, education, and sports.
-
D.
Peter Fleming
Peter Fleming was a British travel writer, journalist, and adventurer, best known for his travel books and for his work as a wartime intelligence officer.
-
E.
Len Deighton
Len Deighton is a British author and historian best known for his spy novels, including "The IPCRESS File," and his influential works on military history.
- 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_69bd440e9d64819083e82cf33b4d9570 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6dde6fcc8190a5aa7587f85632bd |
completed | March 20, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9235e7b8819084fd9eb7c794e0e3 |
completed | March 21, 2026, 12:42 p.m. |
Created at: March 20, 2026, 1:27 p.m.