Triple
T16779387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyoko |
E407816
|
entity |
| Predicate | loyaltyAppearance |
P104367
|
FINISHED |
| Object | appears obedient to Nathan |
—
|
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: appears obedient to Nathan | Statement: [Kyoko, loyaltyAppearance, appears obedient to Nathan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyAppearance Context triple: [Kyoko, loyaltyAppearance, appears obedient to Nathan]
-
A.
loyaltySymbolizedBy
Indicates that an instance of loyalty is represented or expressed by a particular symbol or emblem.
-
B.
loyaltyRevealedIn
chosen
Indicates that an entity’s loyalty becomes evident or is demonstrated through a particular situation, action, or context.
-
C.
loyaltyTheme
Indicates a thematic relationship where one entity is centrally concerned with, expresses, or explores the concept of loyalty in relation to another entity.
-
D.
loyaltyDimension
Indicates the degree or aspect of loyalty characterizing the relationship between entities.
-
E.
isLoyalTo
Indicates that one entity consistently supports, respects, or remains faithful to another entity.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b21401b881909bbbc7382e851a90 |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.