Triple
T17174954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salt Lake City metropolitan area |
E416834
|
entity |
| Predicate | hasPrincipalCity |
P3940
|
FINISHED |
| Object | Layton |
E210251
|
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: Layton | Statement: [Salt Lake City metropolitan area, hasPrincipalCity, Layton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Layton Context triple: [Salt Lake City metropolitan area, hasPrincipalCity, Layton]
-
A.
Layton
chosen
Layton is a rapidly growing suburban city in northern Utah, located along the Wasatch Front and known for its proximity to Hill Air Force Base and the Great Salt Lake.
-
B.
Andre Layton
Andre Layton is the former detective-turned-revolutionary leader aboard the perpetually moving train in the post-apocalyptic TV series "Snowpiercer."
-
C.
Lanning
Lanning is the central protagonist in the game Risk, around whom the primary narrative and strategic conflicts revolve.
-
D.
Lawson
Lawson is a surname most prominently associated with Tina Knowles-Lawson, the fashion designer and mother of Beyoncé and Solange Knowles.
-
E.
Lawson
Lawson is a small city in the U.S. state of Missouri known for its rural community character and local schools.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0c329081909f118bd4b7be8653 |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0148435f6081909bfc6cc1ef59d971 |
completed | May 11, 2026, 3:08 a.m. |
Created at: April 10, 2026, 5:37 a.m.