Triple
T13264002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emily |
E315868
|
entity |
| Predicate | wasTopGivenNameIn |
P26902
|
FINISHED |
| Object | United States late 1990s |
—
|
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 late 1990s | Statement: [Emily, wasTopGivenNameIn, United States late 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasTopGivenNameIn Context triple: [Emily, wasTopGivenNameIn, United States late 1990s]
-
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.
hasNameGivenTo
Indicates that one entity is the name that has been assigned or given to another entity.
-
C.
hasGivenNameTo
Indicates that one entity has assigned or provided a given (first) name to another entity.
-
D.
givenNameIn
Indicates that an entity has a specific first or given name in a particular language or naming context.
-
E.
hasTopness
Indicates that an entity possesses the quantum property of topness, typically associated with the presence or contribution of a top quark.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:25 p.m.