Triple
T1155157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamie |
E23765
|
entity |
| Predicate | hasPopularityNote |
P1755
|
FINISHED |
| Object | common in English-speaking countries |
—
|
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: common in English-speaking countries | Statement: [Jamie, hasPopularityNote, common in English-speaking countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopularityNote Context triple: [Jamie, hasPopularityNote, common in English-speaking countries]
-
A.
peakPopularity
Indicates the time or context in which something reaches its highest level of popularity relative to other times or contexts.
-
B.
popularity
chosen
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
C.
isPopularWith
Indicates that one entity is well-liked, favored, or widely accepted by another entity or group.
-
D.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
E.
hasTouristPopularity
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8fbb548190865b1bf019f2bde4 |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.