Triple
T5022244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union Island |
E112879
|
entity |
| Predicate | otherTown |
P847
|
FINISHED |
| Object | Ashton |
E486833
|
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: Ashton | Statement: [Union Island, otherTown, Ashton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashton Context triple: [Union Island, otherTown, Ashton]
-
A.
Ashton
Ashton is a masculine given name of English origin that has become well known through figures such as actor and entrepreneur Ashton Kutcher.
-
B.
Ashton
Ashton is a small village in the town of Cumberland in Providence County, Rhode Island, known for its historic mill district along the Blackstone River.
-
C.
Ashton
chosen
Ashton is a small coastal town on Union Island in Saint Vincent and the Grenadines, known as one of the island’s main settlements.
-
D.
Ashton
Ashton is a small town in South Africa’s Western Cape, known for its fruit farming and position along the scenic Route 62.
-
E.
Addison
Addison is a Chicago Transit Authority 'L' station on the Blue Line serving the city's Northwest Side.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73656edc8190b802ad38d9552b58 |
completed | March 20, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9c60de2c81908208f93a4bd0ce55 |
completed | March 21, 2026, 1:25 p.m. |
Created at: March 20, 2026, 1:36 p.m.