Triple
T15232806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euron Greyjoy |
E364045
|
entity |
| Predicate | reasonForBanishing |
P36603
|
FINISHED |
| Object | seducing Victarion’s wife |
—
|
LITERAL 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: seducing Victarion’s wife | Statement: [Euron Greyjoy, reasonForBanishing, seducing Victarion’s wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForBanishing Context triple: [Euron Greyjoy, reasonForBanishing, seducing Victarion’s wife]
-
A.
reasonForBan
Indicates the justification or cause that led to an entity being banned.
-
B.
expulsionReason
chosen
Indicates the cause or justification for which an entity was expelled from a group, place, or institution.
-
C.
reasonForExcommunication
Indicates the specific cause or grounds that led to an entity’s excommunication.
-
D.
bannedBy
Indicates that an entity is prohibited or disallowed as a result of a decision or action taken by another entity.
-
E.
reasonForPunishment
Indicates that one entity is the cause, justification, or grounds for another entity receiving a punishment.
- F. None of above.
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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007d7237081908dc17900ee66b64f |
completed | April 15, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:12 a.m.