Triple
T69976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pittsburgh region |
E1400
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Beaver County
Beaver County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
|
E20430
|
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: Beaver County | Statement: [Pittsburgh region, contains, Beaver County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beaver County Context triple: [Pittsburgh region, contains, Beaver County]
-
A.
Washington County
Washington County is a county in southwestern Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
-
B.
Pike County
Pike County is a county in west-central Georgia, United States, known for its rural character and location within the Atlanta metropolitan area’s broader region.
-
C.
Upson County
Upson County is a county in central Georgia, United States, known for its seat in Thomaston and its mix of rural communities and small-town industry.
-
D.
Allegheny County
Allegheny County is a populous county in western Pennsylvania that includes the city of Pittsburgh as its seat and economic center.
-
E.
Putnam County
Putnam County is a suburban county in southeastern New York State known for its lakes, forests, and commuter communities north of New York City.
- 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: Beaver County Triple: [Pittsburgh region, contains, Beaver County]
Generated description
Beaver County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beaver County Target entity description: Beaver County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
-
A.
Washington County
Washington County is a county in southwestern Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
-
B.
Pike County
Pike County is a county in west-central Georgia, United States, known for its rural character and location within the Atlanta metropolitan area’s broader region.
-
C.
Upson County
Upson County is a county in central Georgia, United States, known for its seat in Thomaston and its mix of rural communities and small-town industry.
-
D.
Allegheny County
Allegheny County is a populous county in western Pennsylvania that includes the city of Pittsburgh as its seat and economic center.
-
E.
Putnam County
Putnam County is a suburban county in southeastern New York State known for its lakes, forests, and commuter communities north of New York City.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f045d38819088f5f71e39fa1ee7 |
completed | Feb. 28, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2db50ac3881908088683967e9ae9f |
completed | Feb. 28, 2026, 12:10 p.m. |
| NEDg | Description generation | batch_69a2dbd90d688190b5ed67850db33782 |
completed | Feb. 28, 2026, 12:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2dc3ed95881909c866ee8ebca122f |
completed | Feb. 28, 2026, 12:14 p.m. |
Created at: Feb. 28, 2026, 2:03 a.m.