Triple
T23286719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord of the Treasury |
E589007
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Westminster |
—
|
NE NERFINISHED |
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: Westminster | Statement: [Lord of the Treasury, seat, Westminster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Westminster Context triple: [Lord of the Treasury, seat, Westminster]
-
A.
Westminster
Westminster is a suburban city in the Denver metropolitan area of Colorado, known for its residential communities, parks, and proximity to the Rocky Mountains.
-
B.
Westminster
Westminster is a city in Orange County, California, known for its large Vietnamese-American community and vibrant Little Saigon district.
-
C.
Westminster
chosen
Westminster is a city in northern Maryland that serves as the county seat of Carroll County and a regional hub for the surrounding communities.
-
D.
Westminster
Westminster is a small New England town in northern Massachusetts known for its rural character, historic charm, and proximity to the Wachusett Mountain area.
-
E.
Westminster
Westminster is a small city in Oconee County, South Carolina, known for its historic downtown and annual cultural festivals.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19647178c8190bbca5da38472ce05 |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 5 p.m.