Triple
T32592207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twin Peaks, Washington |
E833100
|
entity |
| Predicate | hasFictionalStateAgencyPresence |
P110922
|
FINISHED |
| Object | FBI |
—
|
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: FBI | Statement: [Twin Peaks, Washington, hasFictionalStateAgencyPresence, FBI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalStateAgencyPresence Context triple: [Twin Peaks, Washington, hasFictionalStateAgencyPresence, FBI]
-
A.
hasFictionalGovernmentAgency
chosen
Indicates that an entity includes, features, or is associated with a government agency that is fictional rather than real.
-
B.
hasFictionalJurisdictionOver
Indicates that one entity holds an imagined or narrative-based authority, control, or legal power over another within a fictional or hypothetical context.
-
C.
hasFictionalCounty
Indicates that one entity includes, is set in, or is associated with a county that is fictional rather than real.
-
D.
hasMemberHeadquartersState
Indicates that the headquarters of a member entity is located within a particular state.
-
E.
hasFictionalPoliceDepartment
Indicates that an entity is associated with or features a police department that exists only within a fictional or imaginary context.
- 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_69f34929ff648190aded9424aa7564ae |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fee0b2da3c8190a3519d0564f2f32d |
completed | May 9, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69fee05b315c819081dfcbfb15273487 |
completed | May 9, 2026, 7:20 a.m. |
Created at: May 1, 2026, 1:05 a.m.