Triple
T23514586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mia Thermopolis |
E574320
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Thermopolis |
—
|
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: Thermopolis | Statement: [Mia Thermopolis, familyName, Thermopolis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thermopolis Context triple: [Mia Thermopolis, familyName, Thermopolis]
-
A.
Thermopolis
chosen
Thermopolis is the surname of Mia Thermopolis, the fictional teenage princess protagonist of Meg Cabot’s "The Princess Diaries" series.
-
B.
Thermopolis, Wyoming
Thermopolis, Wyoming is a small town in north-central Wyoming best known for its large mineral hot springs and proximity to Hot Springs State Park.
-
C.
Laramie
Laramie is a well-equipped, upscale trim level of the Ram 1500 pickup truck known for its added comfort, technology, and premium features.
-
D.
Cheyenne
Cheyenne is the capital and most populous city of Wyoming, known for its historic railroad roots and annual Cheyenne Frontier Days rodeo.
-
E.
Cheyenne
Cheyenne is a Western film written by screenwriter James R. Webb.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa80d9048190ab735dddd301feb4 |
completed | April 29, 2026, 6:51 a.m. |
Created at: April 17, 2026, 6:08 p.m.