Triple
T24768424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omagh Academy |
E619649
|
entity |
| Predicate | drawsPupilsFrom |
P19222
|
FINISHED |
| Object | Omagh |
—
|
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: Omagh | Statement: [Omagh Academy, drawsPupilsFrom, Omagh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drawsPupilsFrom Context triple: [Omagh Academy, drawsPupilsFrom, Omagh]
-
A.
drawsStudentsFrom
chosen
Indicates that an institution or program attracts and enrolls students originating from a particular source, place, or group.
-
B.
hadPupilsFrom
Indicates that an entity served as a teacher or mentor to the specified pupils.
-
C.
drawsVisitorsFrom
Indicates that one place, event, or entity attracts visitors who come from another specified location.
-
D.
hasPupilsGender
Indicates that an entity has pupils whose gender is specified or characterized in some way.
-
E.
drawsCongregantsFrom
Indicates that an organization or religious institution attracts or sources its congregants from a particular group, area, or population.
- 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a8282c81909be28cbb83800ca0 |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:28 a.m.