Triple
T3987600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White |
E86909
|
entity |
| Predicate | frequencyRank |
P29279
|
FINISHED |
| Object | among the most common surnames in the United States |
—
|
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: among the most common surnames in the United States | Statement: [White, frequencyRank, among the most common surnames in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyRank Context triple: [White, frequencyRank, among the most common surnames in the United States]
-
A.
selectionRankingFrequency
Indicates how often an entity is chosen or ranked in a particular position within a selection or ordering process.
-
B.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
C.
frequencyComparedTo
Indicates how often one event or action occurs relative to another, expressing a comparison of their frequencies.
-
D.
frequencyRankInUnitedStates
chosen
Indicates the relative position of something in an ordered list based on how frequently it occurs within the United States.
-
E.
rankSignificance
Indicates how important or influential one entity is relative to others within a specified context or ordering.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.