Triple
T11928264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelly Abagnale |
E283840
|
entity |
| Predicate | realPerson |
P102195
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kelly Abagnale, realPerson, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realPerson Context triple: [Kelly Abagnale, realPerson, true]
-
A.
basedOnRealPersonFor
Indicates that one entity is created, modeled, or inspired using a specific real person as its basis.
-
B.
realName
Indicates that one entity is the actual, full, or birth name of another entity, which may be known by an alias, nickname, or alternate identity.
-
C.
hasPersona
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
-
D.
realPersonAffiliation
Indicates a relationship where a real person is formally associated or connected with an organization, group, or entity.
-
E.
personType
Indicates that an entity is classified as a particular type or category of person.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903024afc8190a97aa3263dc7d017 |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:45 p.m.