Triple
T36666536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Savage |
E905279
|
entity |
| Predicate | fictionalAllegiance |
P96604
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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 | Statement: [Frank Savage, fictionalAllegiance, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalAllegiance Context triple: [Frank Savage, fictionalAllegiance, United States]
-
A.
fictionalCitizenship
chosen
Indicates that an entity is recognized as a citizen of a fictional or imaginary polity, realm, or jurisdiction.
-
B.
fictionalBranch
Indicates that one entity is a branch, division, or offshoot of another within a fictional or imaginary context.
-
C.
fictionalMandate
Indicates that an entity is required or obligated to act according to rules, authority, or conditions that exist only within a fictional or imagined context.
-
D.
fictionalConflict
Indicates a relationship where one fictional entity is in opposition, dispute, or struggle with another within a narrative context.
-
E.
fictionalField
Indicates that the subject is associated with a fictional or imaginary field, domain, or area rather than a real-world one.
- 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_69f76e6f10008190aea41746aa1b186e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff370698ec81909bb1596d7d4112ba |
completed | May 9, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69ff3699b6288190b564839cb05f5cf6 |
completed | May 9, 2026, 1:28 p.m. |
Created at: May 3, 2026, 4:12 p.m.