Triple
T6726737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paoli Station |
E153535
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Paoli |
E227399
|
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: Paoli | Statement: [Paoli Station, formerName, Paoli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paoli Context triple: [Paoli Station, formerName, Paoli]
-
A.
Paoli, Pennsylvania
chosen
Paoli, Pennsylvania is a suburban community in Chester County known as a key stop on the Philadelphia–Harrisburg rail line and part of the Philadelphia metropolitan area.
-
B.
Ephrata
Ephrata is a small city in central Washington State that serves as the county seat of Grant County.
-
C.
Neufchâteau
Neufchâteau is a small historic town in northeastern France known for its role as an administrative and commercial center in the Vosges region.
-
D.
Mattersburg
Mattersburg is a small Austrian town that serves as an important local center in the eastern state of Burgenland.
-
E.
Salisbury, Pennsylvania
Salisbury, Pennsylvania is a small borough in Somerset County best known as the closest town to Mount Davis, the highest point in Pennsylvania.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d152a4908190a041f2049240e7ca |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70afea37881909a4fdce4b3229e38 |
completed | March 27, 2026, 10:55 p.m. |
Created at: March 27, 2026, 2:08 p.m.