Triple
T5810815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nipissing District |
E128862
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Chisholm |
E519043
|
NE 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: Chisholm | Statement: [Nipissing District, hasMunicipality, Chisholm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chisholm Context triple: [Nipissing District, hasMunicipality, Chisholm]
-
A.
Chisholm
chosen
Chisholm is a rural township and small community in northeastern Ontario, Canada, known for its forests, lakes, and agricultural landscape.
-
B.
Chisholm
Chisholm is a residential suburb located in the Maitland region of New South Wales, Australia.
-
C.
Paxton
Paxton is a small rural village in the Scottish Borders region of southeastern Scotland.
-
D.
Paxton
Paxton is a surname most prominently associated with the late American actor and filmmaker Bill Paxton, known for his roles in films like "Twister," "Aliens," and "Titanic."
-
E.
Dirksen
Dirksen is a surname most notably associated with Everett Dirksen, a prominent mid-20th-century American politician and U.S. Senate Minority Leader.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b538cd08190a7dac378898059b9 |
completed | March 22, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c09844f0b881908d4165e550f75d47 |
completed | March 23, 2026, 1:32 a.m. |
Created at: March 22, 2026, 3:52 p.m.