Triple
T4059409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ella |
E84771
|
entity |
| Predicate | popularityInUnitedStates |
P20888
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Ella, popularityInUnitedStates, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularityInUnitedStates Context triple: [Ella, popularityInUnitedStates, high]
-
A.
popularity
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
B.
frequencyRankInUnitedStates
Indicates the relative position of something in an ordered list based on how frequently it occurs within the United States.
-
C.
popularityType
Indicates the specific category or nature of how popularity is characterized or measured in the relationship.
-
D.
popularityContext
Indicates the situational or domain-specific setting in which something’s popularity or level of public favor is evaluated.
-
E.
rankedHighInUS
chosen
Indicates that something has achieved a relatively high ranking or position within the United States according to a specific metric or evaluation.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbd13b4481908f9c09cc4f4a9724 |
completed | March 9, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.