Triple
T11354248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto Christmas tree |
E268910
|
entity |
| Predicate | hasLightingCeremonyAudienceSize |
P15029
|
FINISHED |
| Object | thousands of attendees |
—
|
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: thousands of attendees | Statement: [Toronto Christmas tree, hasLightingCeremonyAudienceSize, thousands of attendees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLightingCeremonyAudienceSize Context triple: [Toronto Christmas tree, hasLightingCeremonyAudienceSize, thousands of attendees]
-
A.
hasAudienceSize
chosen
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
-
B.
hasLightShow
Indicates that an entity features or presents a light-based visual display or performance.
-
C.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
-
D.
supportsAudienceSize
Indicates that one entity is capable of accommodating or handling an audience of a specified size.
-
E.
hasCrowdLevel
Indicates the degree or intensity of how crowded a place, event, or situation is.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.