Triple
T8835446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FrontRunner |
E210255
|
entity |
| Predicate | servesCity |
P82
|
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: [FrontRunner, servesCity, Layton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Layton Context triple: [FrontRunner, servesCity, 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.
Lanning
Lanning is the central protagonist in the game Risk, around whom the primary narrative and strategic conflicts revolve.
-
C.
Lawson
Lawson is a surname most prominently associated with Tina Knowles-Lawson, the fashion designer and mother of Beyoncé and Solange Knowles.
-
D.
Lawson
Lawson is a small town in the Blue Mountains region of New South Wales, Australia, known for its bushwalking trails, waterfalls, and historic village atmosphere.
-
E.
Raydon
Raydon is a small rural village and civil parish in Suffolk, England, known for its countryside setting and historic parish church.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6069ad7881909e31010e73e26f91 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf898022c88190b7274350ce065f00 |
completed | April 3, 2026, 9:33 a.m. |
Created at: March 30, 2026, 6:47 p.m.