Triple
T11786834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westmoreland County |
E280289
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Latrobe |
E354313
|
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: Latrobe | Statement: [Westmoreland County, hasCity, Latrobe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Latrobe Context triple: [Westmoreland County, hasCity, Latrobe]
-
A.
Latrobe
Latrobe is a surname most notably associated with Benjamin Henry Latrobe, a pioneering British-American architect often called the “father of American architecture.”
-
B.
Latrobe
chosen
Latrobe is a small city in Westmoreland County, Pennsylvania, known as the hometown of golfer Arnold Palmer and the birthplace of the banana split.
-
C.
Monongahela, Pennsylvania
Monongahela, Pennsylvania is a small city along the Monongahela River in southwestern Pennsylvania known for its historic downtown and riverfront community.
-
D.
Duquesne
Duquesne is a French noble family name historically associated with military and colonial leadership, notably in 18th-century New France.
-
E.
Duquesne
Duquesne is a small industrial city in Allegheny County, Pennsylvania, historically known for its steel production along the Monongahela River.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a586803481909af0032c35ca6e51 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f090e8828481908baa7f6067190db3 |
completed | April 28, 2026, 10:50 a.m. |
Created at: April 8, 2026, 9:42 p.m.