Triple
T20887336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calgary Heritage |
E514319
|
entity |
| Predicate | provinceOrTerritory |
P766
|
FINISHED |
| Object | Alberta |
—
|
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: Alberta | Statement: [Calgary Heritage, provinceOrTerritory, Alberta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alberta Context triple: [Calgary Heritage, provinceOrTerritory, Alberta]
-
A.
Alberta
chosen
Alberta is a western Canadian province known for its vast prairies, Rocky Mountains, and significant natural resource industries.
-
B.
Alberta
Alberta is a character in August Wilson’s play "Fences," known as the woman with whom Troy Maxson has an extramarital affair, symbolizing his desires and the fractures in his family life.
-
C.
Alberta
"Alberta" is a song featured on the album "Southbound."
-
D.
Saskatchewan
Saskatchewan is a prairie and boreal province in western Canada known for its vast flat landscapes, agriculture, and significant natural resources.
-
E.
Manitoba
Manitoba is a central Canadian province known for its vast prairies, numerous lakes, and northern boreal forests.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d05acf848190a2bbbf33377f23d3 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 12:46 p.m.