Triple
T13626715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee's Summit |
E325601
|
entity |
| Predicate | hasFormerName |
P65
|
FINISHED |
| Object | Strasburg |
E325601
|
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: Strasburg | Statement: [Lee's Summit, hasFormerName, Strasburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Strasburg Context triple: [Lee's Summit, hasFormerName, Strasburg]
-
A.
Strasburg
chosen
Strasburg is the former name of the city now known as Lee's Summit in Missouri, a suburban community in the Kansas City metropolitan area.
-
B.
Strasburg
Strasburg is a surname most prominently associated with Stephen Strasburg, an American former Major League Baseball pitcher known for his time with the Washington Nationals.
-
C.
Strasburg, Virginia
Strasburg, Virginia is a small historic town in the Shenandoah Valley known for its Civil War heritage, mountain scenery, and role as a regional crossroads.
-
D.
Strasburg, Pennsylvania
Strasburg, Pennsylvania is a small historic town in Lancaster County known for its Amish countryside, railroad heritage, and popular train-related attractions.
-
E.
Arlington
Arlington is a major city in the Dallas–Fort Worth metropolitan area known for its sports stadiums, entertainment venues, and rapidly growing population.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbe9c72c88190be3d7a3f2e96afbc |
completed | April 12, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77fa6a46881909d381d76d391f5b7 |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:51 p.m.