Triple
T29628970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan Carty |
E755523
|
entity |
| Predicate | previous employer |
P1910
|
FINISHED |
| Object | Sam Houston State University |
—
|
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: Sam Houston State University | Statement: [Ryan Carty, previous employer, Sam Houston State University]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previous employer Context triple: [Ryan Carty, previous employer, Sam Houston State University]
-
A.
formerEmployer
chosen
Indicates that one entity previously employed the other but no longer does so.
-
B.
parentEmployer
Indicates that one organization is the direct or higher-level employer of another organization or entity.
-
C.
employerPredecessorName
Indicates that the referenced name identifies a previous employer of the entity in question.
-
D.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
E.
previousDepartment
Indicates that an entity was formerly associated with or belonged to a specified department before a change occurred.
- 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_69f0ef88fbe081908f0ad90c1c413f1c |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69fd7b0503a08190ba07338365b6fcc9 |
completed | May 8, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69fd7a9733dc81909199f453c0cc2bc1 |
completed | May 8, 2026, 5:54 a.m. |
Created at: April 28, 2026, 6:39 p.m.