Triple
T30547518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las Vegas (Randall Flagg’s stronghold) |
E777460
|
entity |
| Predicate | countryInRealWorldSetting |
P102287
|
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: [Las Vegas (Randall Flagg’s stronghold), countryInRealWorldSetting, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryInRealWorldSetting Context triple: [Las Vegas (Randall Flagg’s stronghold), countryInRealWorldSetting, United States]
-
A.
countryInReality
chosen
Indicates that a given country exists or is recognized as such within a particular real-world context or scenario.
-
B.
countryInWorld
Indicates that a country is located within and is a member of the world as a whole.
-
C.
situationCountry
Indicates that a particular situation or event is associated with, occurs in, or pertains to a specific country.
-
D.
countryInRealWorldPublishingContext
Indicates the country associated with the real-world context in which a work is published (e.g., where it is issued, distributed, or made available).
-
E.
countryIn
Indicates that one entity is geographically or politically located within the boundaries of a specified country.
- 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_69f2249e19108190a458ab446096bf22 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff80d9a1d88190a95b1488acd6e2e5 |
completed | May 9, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69ff802ae2dc819093a3cda42b63dcbd |
completed | May 9, 2026, 6:42 p.m. |
Created at: April 29, 2026, 8:19 p.m.