Triple
T3540824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bellerophon riding Pegasus |
E74879
|
entity |
| Predicate | typicalAttributesOfRider |
P5084
|
FINISHED |
| Object | armed hero |
—
|
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: armed hero | Statement: [Bellerophon riding Pegasus, typicalAttributesOfRider, armed hero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAttributesOfRider Context triple: [Bellerophon riding Pegasus, typicalAttributesOfRider, armed hero]
-
A.
primaryRiders
Indicates that the referenced entities are the main or principal riders associated with a particular vehicle, trip, or ride-related event.
-
B.
ridershipLevel
Indicates the magnitude or intensity of usage by riders or passengers for a given service, route, or system.
-
C.
supportsRiderCategory
Indicates that one entity is capable of accommodating, enabling, or being compatible with a specified rider category.
-
D.
typicalRiderEmotion
Indicates the characteristic or commonly experienced emotion that a rider typically feels in the context of a particular riding situation or activity.
-
E.
typicalFeatures
chosen
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
- 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_69ad85d274cc8190ab59c97298a1cfbf |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbf729000819086e4fdba9e73e198 |
completed | March 8, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69adae15749881909b847c6ca73c934e |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:20 p.m.