Triple
T38550526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Earl Spilner |
E925096
|
entity |
| Predicate | hasFictionalRecord |
P197301
|
FINISHED |
| Object | clean driving record (cover story) |
—
|
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: clean driving record (cover story) | Statement: [Brian Earl Spilner, hasFictionalRecord, clean driving record (cover story)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalRecord Context triple: [Brian Earl Spilner, hasFictionalRecord, clean driving record (cover story)]
-
A.
hasFictionalDocument
chosen
Indicates that one entity possesses, is associated with, or includes a document that is fictional or exists only within an imagined or narrative context.
-
B.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
C.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
D.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
-
E.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
- 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_69f76eaeb69c8190b367df9330d6f6af |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a009a0e1fa481909ed881012009b268 |
completed | May 10, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_6a0092e9fcb08190a966d720684f25ec |
completed | May 10, 2026, 2:15 p.m. |
Created at: May 3, 2026, 4:32 p.m.