Triple
T1476112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emma |
E30843
|
entity |
| Predicate | wasTopGivenNameInUS |
P26902
|
FINISHED |
| Object | early 2000s |
—
|
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: early 2000s | Statement: [Emma, wasTopGivenNameInUS, early 2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasTopGivenNameInUS Context triple: [Emma, wasTopGivenNameInUS, early 2000s]
-
A.
wasTopGivenNameInCountry
chosen
Indicates that a given name held the highest popularity rank among all given names within a specified country for a particular time period.
-
B.
rankedHighInUS
Indicates that something has achieved a relatively high ranking or position within the United States according to a specific metric or evaluation.
-
C.
isCommonAsFirstName
Indicates that the referenced name is frequently used as a first (given) name within a specified population or context.
-
D.
usedAsSurnameInCountry
Indicates that a particular name functions as a family surname within the specified country.
-
E.
usedAsFirstNameSinceCentury
Indicates that an entity has been used as a first name starting from a specified century.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c602387c8190b97a20c8e05e3d16 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c484e52c81908948ff8c0a42751b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:11 p.m.