Triple
T23496230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Kenneth Stephen |
E571710
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Cambridge |
—
|
NE NERFINISHED |
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: Cambridge | Statement: [James Kenneth Stephen, workLocation, Cambridge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cambridge Context triple: [James Kenneth Stephen, workLocation, Cambridge]
-
A.
Cambridge
Cambridge is a city in southwestern Ontario, Canada, known as part of the Regional Municipality of Waterloo and situated along the Grand River.
-
B.
Cambridge
Cambridge is a historic English city renowned for its prestigious university, medieval architecture, and picturesque riverside setting.
-
C.
Cambridge
Cambridge is a historic English city renowned for its prestigious university, rich academic heritage, and picturesque riverside scenery.
-
D.
Cambridge
Cambridge is a historic English city renowned for its prestigious university, rich academic heritage, and distinctive medieval and riverside architecture.
-
E.
Cambridge
chosen
Cambridge is a historic English city renowned for the University of Cambridge, its centuries-old colleges, and its role as a major center of education, research, and innovation.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7e00384819092729319a378d4ab |
completed | April 29, 2026, 6:40 a.m. |
Created at: April 17, 2026, 6:05 p.m.