Triple
T12074519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto legal district |
E287511
|
entity |
| Predicate | hasTypicalOccupant |
P21135
|
FINISHED |
| Object | lawyers |
—
|
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: lawyers | Statement: [Toronto legal district, hasTypicalOccupant, lawyers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalOccupant Context triple: [Toronto legal district, hasTypicalOccupant, lawyers]
-
A.
hasPrimaryOccupants
chosen
Indicates that certain entities are the main or principal occupants of another entity (such as a space, structure, or location).
-
B.
occupants
Indicates that certain entities are currently inhabiting, residing in, or using a particular place, space, or object.
-
C.
hasNonHumanResident
Indicates that a place or location is inhabited or occupied by one or more non-human entities.
-
D.
occupiedBy
Indicates that a space, position, or role is currently being used, held, or filled by a particular entity.
-
E.
occupiedFrom
Indicates that an entity is in use or inhabited starting from a specified point in time.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.