Triple
T9010674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havre, Montana |
E215461
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object |
Hi-Line
The Hi-Line is a sparsely populated region of northern Montana centered along the BNSF Railway and U.S. Highway 2, known for its small towns, prairie landscapes, and agricultural economy.
|
E772679
|
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: Hi-Line | Statement: [Havre, Montana, locatedOn, Hi-Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hi-Line Context triple: [Havre, Montana, locatedOn, Hi-Line]
-
A.
Haise
Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
-
B.
Deering
Deering is a small Inupiat community and city located on the Seward Peninsula in northwestern Alaska.
-
C.
Dairyland
Dairyland was the former name of the city now known as La Palma in Orange County, California, reflecting its origins as a dairy-farming community.
-
D.
Harline
Harline is a surname most notably associated with Leigh Harline, an American film composer known for his work with Walt Disney Studios.
-
E.
U Line
U Line is a light metro line in the Seoul metropolitan area that serves the city of Uijeongbu with driverless trains on an elevated and mostly automated system.
- 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: Hi-Line Triple: [Havre, Montana, locatedOn, Hi-Line]
Generated description
The Hi-Line is a sparsely populated region of northern Montana centered along the BNSF Railway and U.S. Highway 2, known for its small towns, prairie landscapes, and agricultural economy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hi-Line Target entity description: The Hi-Line is a sparsely populated region of northern Montana centered along the BNSF Railway and U.S. Highway 2, known for its small towns, prairie landscapes, and agricultural economy.
-
A.
Haise
Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
-
B.
Deering
Deering is a small Inupiat community and city located on the Seward Peninsula in northwestern Alaska.
-
C.
Dairyland
Dairyland was the former name of the city now known as La Palma in Orange County, California, reflecting its origins as a dairy-farming community.
-
D.
Harline
Harline is a surname most notably associated with Leigh Harline, an American film composer known for his work with Walt Disney Studios.
-
E.
U Line
U Line is a light metro line in the Seoul metropolitan area that serves the city of Uijeongbu with driverless trains on an elevated and mostly automated system.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69c1571881908d0b144786b5ee1f |
completed | April 1, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdb9dca848190952427bb5712081f |
completed | April 3, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69cfdc5b230881908057cc868e44ea44 |
completed | April 3, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfdcfc28288190b849b3f0216a7e9a |
completed | April 3, 2026, 3:30 p.m. |
Created at: March 30, 2026, 7:06 p.m.