Triple
T12517891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ewing Public Schools |
E299235
|
entity |
| Predicate | studentPopulationServed |
P9355
|
FINISHED |
| Object | children residing in Ewing Township |
—
|
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: children residing in Ewing Township | Statement: [Ewing Public Schools, studentPopulationServed, children residing in Ewing Township]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentPopulationServed Context triple: [Ewing Public Schools, studentPopulationServed, children residing in Ewing Township]
-
A.
servesStudentPopulation
chosen
Indicates that an entity provides services, resources, or support to a defined group of students.
-
B.
studentPopulationLevel
Indicates the relative size or magnitude of the student population associated with an entity.
-
C.
primaryStudentPopulation
Indicates the number or group of students who are enrolled at the primary or elementary level within an educational institution or system.
-
D.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
E.
hasServiceAreaPopulation
Indicates that an entity has a service area characterized by a specific population size or count.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.