Triple
T3038528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ceyx |
E83068
|
entity |
| Predicate | associatedMotive |
P6699
|
FINISHED |
| Object | sea voyage gone wrong |
—
|
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: sea voyage gone wrong | Statement: [Ceyx, associatedMotive, sea voyage gone wrong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedMotive Context triple: [Ceyx, associatedMotive, sea voyage gone wrong]
-
A.
motive
chosen
Indicates the underlying reason, intention, or driving force that explains why an entity performs or is associated with a particular action or event.
-
B.
reasonForAssociation
Indicates that one entity is associated with another due to a specific cause, purpose, or motivating factor underlying their relationship.
-
C.
motivationFor
Indicates that one entity serves as the reason, drive, or incentive behind another entity’s action, state, or occurrence.
-
D.
motivated
Indicates that one entity provides a reason, drive, or incentive that causes another entity to act or behave in a certain way.
-
E.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
- 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b2e03c88190b4e2f01f07c9303a |
completed | March 8, 2026, 3:52 p.m. |
| PD | Predicate disambiguation | batch_69ad961fc62c819087c4c3a44b00847d |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.