Triple
T15465212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playboy |
E372014
|
entity |
| Predicate | hasContributor |
P4244
|
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: [Playboy, hasContributor, Ian Fleming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ian Fleming Context triple: [Playboy, hasContributor, 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.
Peter Fleming
Peter Fleming is a central character in the television series "The Cape," known as a complex and morally ambiguous figure involved in the show's crime-ridden, superhero-driven narrative.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f680cec8190836a5ec841dee224 |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2d01a23c819095cf75b7d5a801a9 |
completed | May 9, 2026, 12:48 p.m. |
Created at: April 10, 2026, 3:33 a.m.