Triple
T5198346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Pennsylvania |
E117328
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | McKeesport |
E144772
|
NE FINISHED |
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: McKeesport | Statement: [Western Pennsylvania, hasMajorCity, McKeesport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McKeesport Context triple: [Western Pennsylvania, hasMajorCity, McKeesport]
-
A.
McKeesport
chosen
McKeesport is a city in southwestern Pennsylvania located near the confluence of the Monongahela and Youghiogheny Rivers, historically known for its steel industry.
-
B.
Aliquippa
Aliquippa is a small industrial city in western Pennsylvania known historically for its steel production and location along the Ohio River.
-
C.
Monessen
Monessen is a small industrial city in western Pennsylvania historically known for its steel production along the Monongahela River.
-
D.
Bessemer, Pennsylvania
Bessemer, Pennsylvania is a small borough in western Pennsylvania known historically for its steel and industrial heritage.
-
E.
Birmingham, Pennsylvania
Birmingham, Pennsylvania is a small historic borough in Huntingdon County best known as the birthplace of food industry pioneer Henry John Heinz.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd4462ed04819084fcb01eb9d2fa74 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a1f154481908be5d3c9cbbef92a |
completed | March 20, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef7fcae508190bffd21937488d674 |
completed | March 21, 2026, 7:56 p.m. |
Created at: March 20, 2026, 1:47 p.m.