Triple
T631413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grant County, Washington |
E15933
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ephrata
Ephrata is a small city in central Washington State that serves as the county seat of Grant County.
|
E80061
|
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: Ephrata | Statement: [Grant County, Washington, contains, Ephrata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ephrata Context triple: [Grant County, Washington, contains, Ephrata]
-
A.
Mount Pleasant, Pennsylvania
Mount Pleasant, Pennsylvania is a small borough in Westmoreland County known historically for its coal mining and glass manufacturing industries.
-
B.
Warminster, Pennsylvania
Warminster, Pennsylvania is a suburban township in Bucks County, known as a residential community within the greater Philadelphia metropolitan area.
-
C.
Phillippi
Phillippi is a surname most notably associated with early 20th-century American baseball pitcher Deacon Phillippe.
-
D.
Upland, Pennsylvania
Upland, Pennsylvania is a small borough in Delaware County known historically as the home of the former Crozer Theological Seminary, where Martin Luther King Jr. once studied.
-
E.
Langhorne
Langhorne is the middle name of Samuel Langhorne Clemens, better known by his pen name Mark Twain, the famed American author and humorist.
- 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: Ephrata Triple: [Grant County, Washington, contains, Ephrata]
Generated description
Ephrata is a small city in central Washington State that serves as the county seat of Grant County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ephrata Target entity description: Ephrata is a small city in central Washington State that serves as the county seat of Grant County.
-
A.
Mount Pleasant, Pennsylvania
Mount Pleasant, Pennsylvania is a small borough in Westmoreland County known historically for its coal mining and glass manufacturing industries.
-
B.
Warminster, Pennsylvania
Warminster, Pennsylvania is a suburban township in Bucks County, known as a residential community within the greater Philadelphia metropolitan area.
-
C.
Phillippi
Phillippi is a surname most notably associated with early 20th-century American baseball pitcher Deacon Phillippe.
-
D.
Upland, Pennsylvania
Upland, Pennsylvania is a small borough in Delaware County known historically as the home of the former Crozer Theological Seminary, where Martin Luther King Jr. once studied.
-
E.
Langhorne
Langhorne is the middle name of Samuel Langhorne Clemens, better known by his pen name Mark Twain, the famed American author and humorist.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ec171008190ab91dee86e9279af |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a57403c0208190b3ff497aade61b29 |
completed | March 2, 2026, 11:26 a.m. |
| NEDg | Description generation | batch_69a574d565c481908ce2b259cb6e6977 |
completed | March 2, 2026, 11:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5757b7f2881909caf99470b08e811 |
completed | March 2, 2026, 11:33 a.m. |
Created at: March 1, 2026, 7:35 p.m.