Triple
T8757266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | south-central Idaho |
E208101
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Rupert
Rupert is a small agricultural city in south-central Idaho known for its historic town square and role as a local farming hub.
|
E754643
|
NE FINISHED |
How this triple was built (4 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: Rupert | Statement: [south-central Idaho, hasCity, Rupert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rupert Context triple: [south-central Idaho, hasCity, Rupert]
-
A.
Rupert
Rupert is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by various notable figures.
-
B.
Rupert
Rupert is a small town located in Greenbrier County in the state of West Virginia, United States.
-
C.
Rupert Griffin
Rupert Griffin is known primarily as the brother of American actress and 1950s film star Debra Paget.
-
D.
Rupert Macabee
Rupert Macabee is a character in the 1957 Charlie Chaplin film "A King in New York," appearing in its satirical portrayal of politics and media in postwar America.
-
E.
Ralph of Upmeads
Ralph of Upmeads is the adventurous young knight-errant who journeys across perilous lands in William Morris’s fantasy romance "The Well at the World’s End" in search of a legendary life-giving well.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rupert Triple: [south-central Idaho, hasCity, Rupert]
Generated description
Rupert is a small agricultural city in south-central Idaho known for its historic town square and role as a local farming hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rupert Target entity description: Rupert is a small agricultural city in south-central Idaho known for its historic town square and role as a local farming hub.
-
A.
Rupert
Rupert is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by various notable figures.
-
B.
Rupert
Rupert is a small town located in Greenbrier County in the state of West Virginia, United States.
-
C.
Rupert Griffin
Rupert Griffin is known primarily as the brother of American actress and 1950s film star Debra Paget.
-
D.
Rupert Macabee
Rupert Macabee is a character in the 1957 Charlie Chaplin film "A King in New York," appearing in its satirical portrayal of politics and media in postwar America.
-
E.
Ralph of Upmeads
Ralph of Upmeads is the adventurous young knight-errant who journeys across perilous lands in William Morris’s fantasy romance "The Well at the World’s End" in search of a legendary life-giving well.
- F. None of above. chosen
Provenance (5 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_69ca835cd6b08190bd7c63db92f53c86 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5ddabdc88190ba50ef1833a815d0 |
completed | March 31, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf4338c0f88190a1e3f7ef164b6c6d |
completed | April 3, 2026, 4:34 a.m. |
| NEDg | Description generation | batch_69cf452b237c8190958f7b42e9611e7b |
completed | April 3, 2026, 4:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf45e6f4108190ac6955264b466abb |
completed | April 3, 2026, 4:45 a.m. |
Created at: March 30, 2026, 6:40 p.m.