Triple
T11473272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love It or List It |
E271961
|
entity |
| Predicate | alsoSetIn |
P54147
|
FINISHED |
| Object | surrounding areas of Toronto |
—
|
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: surrounding areas of Toronto | Statement: [Love It or List It, alsoSetIn, surrounding areas of Toronto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoSetIn Context triple: [Love It or List It, alsoSetIn, surrounding areas of Toronto]
-
A.
setsIn
chosen
Indicates that one entity places or positions another entity into or within a specified container, location, or context.
-
B.
addedFor
Indicates that one entity was created, included, or introduced specifically for the benefit, use, or purpose of another entity.
-
C.
alsoMetAt
Indicates that the same entities met together at an additional, distinct place or event beyond a previously mentioned meeting location.
-
D.
alsoUsedIn
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
-
E.
alsoHolds
Indicates that a condition, property, or relation that applies in one context or case simultaneously applies in another context or case.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294b3f388190a587c358313f7260 |
completed | April 9, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69d8086ecd6c81908f424864857762d6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.