Triple
T5150952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Ledger |
E116190
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Cambridge |
E492
|
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: Cambridge | Statement: [Philip Ledger, workLocation, Cambridge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cambridge Context triple: [Philip Ledger, workLocation, Cambridge]
-
A.
Cambridge
Cambridge is a town in New Zealand known for its picturesque rural setting, equestrian culture, and proximity to the Waikato River.
-
B.
Cambridge
Cambridge is a historic and academically renowned city in Massachusetts, best known as the home of Harvard University and the Massachusetts Institute of Technology (MIT).
-
C.
Cambridge
Cambridge is a prominent city in the Greater Boston area best known as the home of Harvard University and the Massachusetts Institute of Technology (MIT).
-
D.
Cambridge
Cambridge is a city in southwestern Ontario, Canada, known as part of the Regional Municipality of Waterloo and situated along the Grand River.
-
E.
Cambridge, England
chosen
Cambridge, England is a historic university city on the River Cam renowned for the University of Cambridge and its longstanding contributions to education, science, and culture.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd78d965548190b09f574acf3b9b1a |
completed | March 20, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beef9de9c88190b06c5076e5eabe3e |
completed | March 21, 2026, 7:21 p.m. |
Created at: March 20, 2026, 1:44 p.m.