Triple
T28490876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latymer School, Edmonton |
E720958
|
entity |
| Predicate | hasSpecialCharacteristic |
P32672
|
FINISHED |
| Object | highly oversubscribed |
—
|
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: highly oversubscribed | Statement: [Latymer School, Edmonton, hasSpecialCharacteristic, highly oversubscribed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpecialCharacteristic Context triple: [Latymer School, Edmonton, hasSpecialCharacteristic, highly oversubscribed]
-
A.
hasSpecial
chosen
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
B.
hasHumanCharacteristic
Indicates that an entity possesses a trait, quality, or behavior typically associated with humans.
-
C.
subjectHasCharacteristic
Indicates that a subject possesses, exhibits, or is defined by a particular characteristic or attribute.
-
D.
hasSpecials
Indicates that an entity offers or is associated with special deals, promotions, or limited-time offers.
-
E.
hasSpecialCategory
Indicates that an entity is associated with a designated special or exceptional category distinct from its standard classifications.
- 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_69f01a5a47148190b0a7e111bc432e0a |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
Created at: April 28, 2026, 3:01 a.m.