Triple
T10070404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyle Pratt |
E213607
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Pratt |
E383357
|
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: Pratt | Statement: [Kyle Pratt, familyName, Pratt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pratt Context triple: [Kyle Pratt, familyName, Pratt]
-
A.
Pratt
chosen
Pratt is a common English surname borne by various notable individuals across fields such as entertainment, politics, and academia.
-
B.
Princeton
Princeton is a historic New Jersey town best known as the site of the pivotal 1777 Battle of Princeton during the American Revolutionary War and as home to Princeton University.
-
C.
Princeton
Princeton is a small but rapidly growing city in Collin County, Texas, situated in the northeastern part of the Dallas–Fort Worth metropolitan area.
-
D.
Princeton
Princeton is a small unincorporated community in Colusa County, California, known for its agricultural surroundings in the Sacramento Valley.
-
E.
Princeton
Princeton is a small city in central Wisconsin known for its historic downtown, outdoor recreation along the Fox River, and popular weekly flea market.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcffa045c8190a08db0bb74cb006a |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d29aa05cc881909f59178e9c6c01ef |
completed | April 5, 2026, 5:23 p.m. |
Created at: March 30, 2026, 8:58 p.m.