Triple
T2104077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kings County |
E37153
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kensington |
E179110
|
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: Kensington | Statement: [Kings County, contains, Kensington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kensington Context triple: [Kings County, contains, Kensington]
-
A.
Kensington
Kensington is a district in West London, England, known for its affluent residential areas, cultural institutions, and royal associations.
-
B.
Kensington
chosen
Kensington is a small, affluent unincorporated community in Contra Costa County, California, located in the San Francisco Bay Area.
-
C.
Kensington
Kensington is a popular inner-city district in Calgary known for its vibrant mix of shops, restaurants, and cultural venues.
-
D.
Hampstead
Hampstead is a historic and affluent district in north London, England, known for its literary and artistic associations and the expansive Hampstead Heath.
-
E.
Hampstead
Hampstead is a small, affluent residential town on the Island of Montreal in Quebec, Canada, known for its suburban character and tree-lined streets.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbabf7cdc81909636dff34badc1c5 |
completed | March 7, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2b5824ac81909f071511907145e8 |
completed | March 9, 2026, 8:19 p.m. |
Created at: March 4, 2026, 7:43 p.m.