Triple
T23306945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marietta Edgecombe |
E590470
|
entity |
| Predicate | reasonForJoiningDA |
P30267
|
FINISHED |
| Object | persuaded by Cho Chang |
—
|
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: persuaded by Cho Chang | Statement: [Marietta Edgecombe, reasonForJoiningDA, persuaded by Cho Chang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForJoiningDA Context triple: [Marietta Edgecombe, reasonForJoiningDA, persuaded by Cho Chang]
-
A.
reasonForPledge
Indicates the motivation or justification behind making a particular pledge or commitment.
-
B.
reasonForEnlistment
Indicates the motivation, cause, or circumstances that led an individual to join a military or similar organized service.
-
C.
reasonForAssociation
chosen
Indicates that one entity is associated with another due to a specific cause, purpose, or motivating factor underlying their relationship.
-
D.
reasonForLeaving
Indicates the cause, motivation, or circumstance that led an entity to depart or discontinue an association, position, or place.
-
E.
reasonForAssumingOffice
Indicates the circumstance, cause, or justification that led an entity to take up or begin holding a particular office or position.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1972846fc819092ca2b9590b2e177 |
completed | April 29, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:05 p.m.