Triple
T20879208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Enemy No. 1 (FBI label for John Dillinger) |
E514098
|
entity |
| Predicate | appliedToPersonBirthYear |
P11702
|
FINISHED |
| Object | 1903 |
—
|
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: 1903 | Statement: [Public Enemy No. 1 (FBI label for John Dillinger), appliedToPersonBirthYear, 1903]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToPersonBirthYear Context triple: [Public Enemy No. 1 (FBI label for John Dillinger), appliedToPersonBirthYear, 1903]
-
A.
appliesToPersonBirthName
Indicates that the referenced value is used as the birth name of the specified person.
-
B.
yearOfBirth
Indicates the specific calendar year in which an entity was born.
-
C.
notableBearerBirthYear
chosen
Indicates the year in which a notable bearer of the referenced name, title, or identifier was born.
-
D.
authorBirthYear
Indicates the year in which the author of a work or text was born.
-
E.
hasPerformerBirthYear
Indicates that a performer is associated with a specific year in which they were born.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c678b394819096a17de9e04cd74f |
completed | April 21, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:45 p.m.