Triple
T19648041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zelda Fuller |
E471731
|
entity |
| Predicate | loyal |
P94124
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Zelda Fuller, loyal, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyal Context triple: [Zelda Fuller, loyal, true]
-
A.
allegiance
Indicates a relationship where one entity is loyal, committed, or obligated in support or service to another entity.
-
B.
isLoyalTo
chosen
Indicates that one entity consistently supports, respects, or remains faithful to another entity.
-
C.
loyaltyToSpouse
Indicates a committed, faithful allegiance and support that one spouse maintains toward the other within their marital relationship.
-
D.
hadAllegiance
Indicates that an entity was loyally committed or formally bound in support or service to another entity, such as a person, group, or cause.
-
E.
loyaltyConflict
Indicates a situation where an entity’s loyalties to different people, groups, or principles are in tension or opposition, creating a conflict in choosing whom or what to support.
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64126cea88190a1a6929f46de4686 |
completed | April 20, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.