Triple
T10451781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burrillville |
E246441
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object | Nasonville |
E245657
|
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: Nasonville | Statement: [Burrillville, hasVillage, Nasonville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nasonville Context triple: [Burrillville, hasVillage, Nasonville]
-
A.
Nasonville
chosen
Nasonville is a village and census-designated place in the town of Burrillville in northern Rhode Island.
-
B.
Tenneville
Tenneville is a rural municipality in the Ardennes region of southern Belgium, known for its forests and small villages.
-
C.
Snowville
Snowville is a small rural settlement located within the township of Tehkummah in Ontario, Canada.
-
D.
Hiesville
Hiesville is a small commune in the Manche department of northwestern France, notable for its location in the historic Normandy region.
-
E.
Blissville
Blissville is a small, historically industrial neighborhood in western Queens, New York City, known for its proximity to major rail yards and cemeteries.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0b7bb481908182c7b9a80af3b3 |
completed | April 7, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87efedf6c8190aa4b7bbe5f160eeb |
completed | April 10, 2026, 4:39 a.m. |
Created at: April 6, 2026, 12:17 p.m.