Triple
T12167083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lingleville, Texas |
E289860
|
entity |
| Predicate | schoolGradesOffered |
P3870
|
FINISHED |
| Object | pre-kindergarten through 12 |
—
|
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: pre-kindergarten through 12 | Statement: [Lingleville, Texas, schoolGradesOffered, pre-kindergarten through 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: schoolGradesOffered Context triple: [Lingleville, Texas, schoolGradesOffered, pre-kindergarten through 12]
-
A.
schoolTypeOffered
Indicates the specific type or category of school that is provided or made available by an educational institution or organization.
-
B.
servesGradeLevels
chosen
Indicates that an entity (such as a school or program) provides services or instruction to students in the specified grade levels.
-
C.
offersGrades
Indicates that one entity provides or assigns academic grades to another entity.
-
D.
eligibleGradeLevels
Indicates the grade levels for which something (such as a program, course, or benefit) is considered eligible or applicable.
-
E.
schoolYear
Indicates the academic year or grade level in which an entity (typically a student or class) is situated within an educational system.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91621ca6c81908365732f361aef13 |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150e85348190b9b47cda4a17dcd0 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.