Triple
T2651609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Tanner |
E53910
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object | Jon Snow |
E285878
|
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: Jon Snow | Statement: [Karl Tanner, enemyOf, Jon Snow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jon Snow Context triple: [Karl Tanner, enemyOf, Jon Snow]
-
A.
Jon Snow
chosen
Jon Snow is a central character in the "Game of Thrones" series, a member of the Night's Watch who rises to leadership and plays a crucial role in the struggle for the fate of Westeros.
-
B.
Eddard Stark
Eddard Stark is the honorable and stoic Lord of Winterfell and Warden of the North in the fantasy series "A Song of Ice and Fire" and its television adaptation "Game of Thrones."
-
C.
Robb
Robb is a given name, typically a variant of the name Rob or Robert, used as a masculine first name or surname.
-
D.
Meter Theon
Meter Theon is an ancient Greek mother goddess associated with the earth and often identified with deities such as Rhea or Cybele, venerated in sanctuaries like the Metroon at Olympia.
-
E.
Aegon
Aegon is a multinational life insurance, pensions, and asset management company headquartered in the Netherlands.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd93071248190820197936e3167f7 |
completed | March 7, 2026, 7:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afa052c91c8190abfd49dbc62a4448 |
completed | March 10, 2026, 4:38 a.m. |
Created at: March 6, 2026, 9:53 p.m.