Triple
T2839072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Mirvish Theatre |
E62419
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Toronto theatre district |
E291117
|
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: Toronto theatre district | Statement: [Ed Mirvish Theatre, partOf, Toronto theatre district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toronto theatre district Context triple: [Ed Mirvish Theatre, partOf, Toronto theatre district]
-
A.
Downtown Toronto
Downtown Toronto is the city’s primary central business district and cultural core, known for its dense skyline, major attractions, and vibrant urban life.
-
B.
Toronto
Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
-
C.
Midtown Toronto
Midtown Toronto is a central district of Toronto known for its mix of residential neighborhoods, historic landmarks, and vibrant commercial areas.
-
D.
Toronto Entertainment District
chosen
The Toronto Entertainment District is a vibrant downtown neighborhood known for its theaters, nightlife, sports venues, and major cultural attractions.
-
E.
Toronto legal district
The Toronto legal district is a downtown area that houses many of the city’s major courts, law firms, and legal institutions.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdef145f08190be8556bc696ba3ab |
completed | March 7, 2026, 8:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8cf32d08190bda89a513082813f |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 10:01 p.m.