Triple
T15127136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sigyn |
E361318
|
entity |
| Predicate | loyaltyExhibited |
P94124
|
FINISHED |
| Object | remains with Loki despite his crimes |
—
|
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: remains with Loki despite his crimes | Statement: [Sigyn, loyaltyExhibited, remains with Loki despite his crimes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyExhibited Context triple: [Sigyn, loyaltyExhibited, remains with Loki despite his crimes]
-
A.
isLoyalTo
chosen
Indicates that one entity consistently supports, respects, or remains faithful to another entity.
-
B.
loyaltyDimension
Indicates the degree or aspect of loyalty characterizing the relationship between entities.
-
C.
loyaltyRevealedIn
Indicates that an entity’s loyalty becomes evident or is demonstrated through a particular situation, action, or context.
-
D.
loyaltyReason
Indicates the reason or motivation behind one entity’s loyalty or allegiance to another.
-
E.
loyaltyIncentive
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005a1b9288190954f2d92549805e5 |
completed | April 15, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:06 a.m.