Triple
T15488129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parks Road |
E377104
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | City of Oxford |
E19137
|
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: City of Oxford | Statement: [Parks Road, locatedIn, City of Oxford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Oxford Context triple: [Parks Road, locatedIn, City of Oxford]
-
A.
Oxford
chosen
Oxford is a historic English city renowned for its prestigious university, distinctive architecture, and long-standing academic and cultural influence.
-
B.
Oxford
Oxford is a federal electoral district in Ontario, Canada, represented in the House of Commons.
-
C.
Oxford
Oxford is a small Mississippi city best known as the home of the University of Mississippi and for its rich literary and cultural heritage.
-
D.
Oxford
Oxford is a small town in New Haven County, Connecticut, known for its suburban-rural character and growing residential communities.
-
E.
Oxford
Oxford is a small borough in southeastern Pennsylvania known for its historic downtown and proximity to several colleges and rural communities.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03faaca588190b0397bc2e27a522a |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff365d45488190b48458092b6ffead |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 3:48 a.m.