Triple
T9652733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Appointments Office (Texas Governor) |
E233374
|
entity |
| Predicate | typeOfAppointmentHandled |
P12376
|
FINISHED |
| Object | appointments to state boards |
—
|
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: appointments to state boards | Statement: [Appointments Office (Texas Governor), typeOfAppointmentHandled, appointments to state boards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAppointmentHandled Context triple: [Appointments Office (Texas Governor), typeOfAppointmentHandled, appointments to state boards]
-
A.
appointmentType
chosen
Indicates the specific category or nature of an appointment associated with an entity or event.
-
B.
typeOfProcedureHandled
Indicates the specific kind or category of procedure that an entity is responsible for managing or processing.
-
C.
typicalAppointment
Indicates that an appointment represents a standard, usual, or commonly occurring scheduling arrangement between entities.
-
D.
appointerType
Indicates the role or category of entity that has the authority to appoint another entity.
-
E.
appointmentsInvolve
Indicates that scheduled appointments include or engage specific participants, resources, or activities in the appointment event.
- 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_69ca848c1ba88190b84b410cd14627fc |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9bb26b748190bc32e2003829b0ec |
completed | April 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b0263081908cf6df3eb07d71b0 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:13 p.m.