Triple
T38665037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia |
E940430
|
entity |
| Predicate | rankedInTop100BabyNames |
P191495
|
FINISHED |
| Object | United States 20th century |
—
|
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: United States 20th century | Statement: [Virginia, rankedInTop100BabyNames, United States 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankedInTop100BabyNames Context triple: [Virginia, rankedInTop100BabyNames, United States 20th century]
-
A.
wasTopRankedNameInCountry
Indicates that a given name held the highest popularity ranking within a specified country during a particular time period.
-
B.
nationalPopularity
Indicates the degree to which something is liked, recognized, or supported by people across an entire nation.
-
C.
namePopularityRegion
Indicates the geographic region or area in which a particular name has a certain level of popularity or usage.
-
D.
wasTopGivenNameInCountry
Indicates that a given name held the highest popularity rank among all given names within a specified country for a particular time period.
-
E.
namePopularityType
Indicates the category or type of popularity associated with a given name (e.g., how or in what way the name is considered popular).
- F. None of above. chosen
Provenance (4 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdfbafbf48190abe38ec0003a6419 |
completed | May 7, 2026, 6:53 p.m. |
Created at: May 3, 2026, 4:33 p.m.