Triple
T24466186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garrus Vakarian |
E616975
|
entity |
| Predicate | loyaltyMissionName |
P156209
|
FINISHED |
| Object | Eye for an Eye |
—
|
NE NERFINISHED |
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: Eye for an Eye | Statement: [Garrus Vakarian, loyaltyMissionName, Eye for an Eye]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyMissionName Context triple: [Garrus Vakarian, loyaltyMissionName, Eye for an Eye]
-
A.
loyaltyPointName
Indicates the designated name or label assigned to a specific type or category of loyalty points in a loyalty program.
-
B.
loyaltyProgramName
Indicates that an entity is associated with or identified by the name of a specific loyalty or rewards program.
-
C.
loyaltySymbolizedBy
Indicates that an instance of loyalty is represented or expressed by a particular symbol or emblem.
-
D.
loyaltyIncentive
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
-
E.
loyaltyGoal
Indicates that one entity has the objective or commitment to remain faithful, supportive, or devoted to another entity or cause.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2993ecd988190991598832b29a131 |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:20 a.m.