Triple
T34508911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Town |
E885965
|
entity |
| Predicate | hasNearbyFederalLandmarks |
P201134
|
FINISHED |
| Object | Parliament of Canada buildings |
—
|
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: Parliament of Canada buildings | Statement: [Lower Town, hasNearbyFederalLandmarks, Parliament of Canada buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyFederalLandmarks Context triple: [Lower Town, hasNearbyFederalLandmarks, Parliament of Canada buildings]
-
A.
hasNearbyMemorials
Indicates that one or more memorials are located in close physical proximity to the referenced entity.
-
B.
hasNearbyHistoricStructure
Indicates that one entity is located close to another entity that is classified as a historic structure.
-
C.
hasFormerNearbyLandmark
Indicates that an entity previously had a nearby landmark that no longer exists or no longer holds the same status or relevance.
-
D.
hasNearbyHistoricArea
Indicates that one entity is located close to another entity that is designated as a historic area.
-
E.
distanceFromFord’sTheatre
Indicates the spatial distance between an entity and Ford’s Theatre.
- F. None of above. chosen
Provenance (4 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_69f349cc0220819081f154c6964f4dc2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffcb5536d88190bfc2e00b854cacfb |
completed | May 10, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69ffc900c2a081909dea04aa60566923 |
completed | May 9, 2026, 11:53 p.m. |
| PDg | Predicate description generation | batch_69ffcb5428b88190b154776ebcbb81e1 |
completed | May 10, 2026, 12:03 a.m. |
Created at: May 1, 2026, 2:01 a.m.