Triple
T14366723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jorah Mormont |
E356252
|
entity |
| Predicate | loyaltyTheme |
P113752
|
FINISHED |
| Object | unrequited love and redemption |
—
|
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: unrequited love and redemption | Statement: [Jorah Mormont, loyaltyTheme, unrequited love and redemption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyTheme Context triple: [Jorah Mormont, loyaltyTheme, unrequited love and redemption]
-
A.
loyaltySymbolizedBy
Indicates that an instance of loyalty is represented or expressed by a particular symbol or emblem.
-
B.
loyaltyDimension
Indicates the degree or aspect of loyalty characterizing the relationship between entities.
-
C.
loyaltyIncentive
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
-
D.
loyaltyMechanism
Indicates a mechanism or process through which loyalty is established, maintained, or reinforced between entities.
-
E.
loyaltyProgramFocus
Indicates that an entity’s primary emphasis or activity is centered on managing, offering, or optimizing a loyalty or rewards program.
- F. None of above. chosen
Provenance (4 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8faf00e8819087d7100e9d8c1877 |
completed | April 14, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:15 a.m.