Triple
T14197233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuneaton railway station |
E351867
|
entity |
| Predicate | hasServiceTo |
P6787
|
FINISHED |
| Object | Stafford |
E134052
|
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: Stafford | Statement: [Nuneaton railway station, hasServiceTo, Stafford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stafford Context triple: [Nuneaton railway station, hasServiceTo, Stafford]
-
A.
Stafford
Stafford is a county in Northern Virginia known for its suburban communities, historical sites, and proximity to Washington, D.C.
-
B.
Stafford
chosen
Stafford is a historic market town in Staffordshire, England, known for its medieval castle, role as the county town, and long-standing regional administrative importance.
-
C.
Stafford
Stafford is a small rural community located within the Township of South Dundas in eastern Ontario, Canada.
-
D.
Stafford
Stafford is a surname of English origin borne by numerous notable individuals, including politicians, athletes, and artists.
-
E.
Bedford
Bedford is a small suburban city located in northeastern Ohio within the Greater Cleveland metropolitan area.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61e30f208190b61c1c7bd3501156 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd280aaa1c8190a957dfc2c624e3f6 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:04 a.m.