Triple
T6179460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dukes Theatre |
E137902
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Lancaster |
E24581
|
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: Lancaster | Statement: [Dukes Theatre, locatedIn, Lancaster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lancaster Context triple: [Dukes Theatre, locatedIn, Lancaster]
-
A.
Lancaster
chosen
Lancaster is a historic city in North West England known for its medieval castle, Georgian architecture, and role as the county town of Lancashire.
-
B.
Lancaster
Lancaster is a suburban city in the Dallas–Fort Worth metropolitan area known for its residential communities and proximity to Dallas.
-
C.
Lancaster
Lancaster is a city in northern Los Angeles County, California, known for its location in the Antelope Valley of the Mojave Desert and its aerospace and renewable energy industries.
-
D.
Lancaster
Lancaster was the original settlement that later developed into the city of Lincoln, the capital of Nebraska.
-
E.
Lancaster
Lancaster is an English surname most famously associated with the American actor Burt Lancaster.
- 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_69c008a80f748190ba3d07ffc81acb29 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05dcb77948190b5385438f81bf0a8 |
completed | March 22, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1414ea324819087dc9267938efb5c |
completed | March 23, 2026, 1:34 p.m. |
Created at: March 22, 2026, 4:18 p.m.