Triple
T150689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clementine |
E3423
|
entity |
| Predicate | hasPopularity |
P1755
|
FINISHED |
| Object | used 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: used in English-speaking countries | Statement: [Clementine, hasPopularity, used in English-speaking countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopularity Context triple: [Clementine, hasPopularity, used in English-speaking countries]
-
A.
isPopularWith
Indicates that one entity is well-liked, favored, or widely accepted by another entity or group.
-
B.
popularity
chosen
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
C.
peakPopularity
Indicates the time or context in which something reaches its highest level of popularity relative to other times or contexts.
-
D.
popularInPeriod
Indicates that something is widely liked, used, or influential during a specified time period.
-
E.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565adaf48190b68ae4444ff83ccd |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.