Triple
T17890818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMERSH (in the novel) |
E447309
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object |
General G
General G is a high-ranking, shadowy Soviet intelligence officer in Ian Fleming’s James Bond novel "From Russia, with Love," serving as a key figure within the counterintelligence organization SMERSH.
|
E1293993
|
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: General G | Statement: [SMERSH (in the novel), associatedWithCharacter, General G]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: General G Context triple: [SMERSH (in the novel), associatedWithCharacter, General G]
-
A.
General Re
General Re is a major global property and casualty reinsurance company and a wholly owned subsidiary of Berkshire Hathaway.
-
B.
Gu
Gu is a Korean family name that can also be transliterated as Koo in the Latin alphabet.
-
C.
General
A General is a high-ranking military officer, typically commanding large units or formations and serving as one of the senior leaders within an armed force.
-
D.
GV
GV is the venture capital investment arm of Alphabet Inc., focused on funding and supporting innovative technology startups.
-
E.
GV
GV is a common shorthand nickname for Grand Valley State University, a public university in Allendale, Michigan.
- 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: General G Triple: [SMERSH (in the novel), associatedWithCharacter, General G]
Generated description
General G is a high-ranking, shadowy Soviet intelligence officer in Ian Fleming’s James Bond novel "From Russia, with Love," serving as a key figure within the counterintelligence organization SMERSH.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: General G Target entity description: General G is a high-ranking, shadowy Soviet intelligence officer in Ian Fleming’s James Bond novel "From Russia, with Love," serving as a key figure within the counterintelligence organization SMERSH.
-
A.
General Re
General Re is a major global property and casualty reinsurance company and a wholly owned subsidiary of Berkshire Hathaway.
-
B.
Gu
Gu is a Korean family name that can also be transliterated as Koo in the Latin alphabet.
-
C.
General
A General is a high-ranking military officer, typically commanding large units or formations and serving as one of the senior leaders within an armed force.
-
D.
GV
GV is the venture capital investment arm of Alphabet Inc., focused on funding and supporting innovative technology startups.
-
E.
GV
GV is a common shorthand nickname for Grand Valley State University, a public university in Allendale, Michigan.
- 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_69d8b9f59bd48190a6fc925a855b8bac |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49d7948888190b59ddc7061d13e84 |
completed | April 19, 2026, 9:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0313e10c40819089cb912a020b32de |
completed | May 12, 2026, 11:49 a.m. |
| NEDg | Description generation | batch_6a031528abac8190b5257eff1647b6b3 |
completed | May 12, 2026, 11:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03164881ec8190a783b095f3cf47b3 |
completed | May 12, 2026, noon |
Created at: April 10, 2026, 10:18 a.m.