Triple
T10340894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarendon Laboratory |
E243124
|
entity |
| Predicate | locatedOnStreet |
P959
|
FINISHED |
| Object | Parks Road |
E377104
|
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: Parks Road | Statement: [Clarendon Laboratory, locatedOnStreet, Parks Road]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parks Road Context triple: [Clarendon Laboratory, locatedOnStreet, Parks Road]
-
A.
Parks Road
chosen
Parks Road is a major street in central Oxford, England, running through the university area and lined with prominent academic buildings and museums.
-
B.
Brimley Road
Brimley Road is a major north–south arterial street in Toronto, Ontario, running through neighborhoods such as Agincourt in the city's east end.
-
C.
Kelsey Road
Kelsey Road is a local roadway serving as a primary access route to and through the village of Port Barrington, Illinois.
-
D.
Naylor Road
Naylor Road is a street in the Washington, D.C. area that lends its name to the nearby Naylor Road Metro station on the Green Line.
-
E.
Patterson Road
Patterson Road is a significant thoroughfare running through the Oakwood area of Montgomery County, Ohio, serving as a key local connector for residential and commercial traffic.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e0a645348190af91450360a9abed |
completed | April 7, 2026, 10:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f03e00c819091ae5273aa10fe4b |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 6, 2026, 11:55 a.m.