Triple
T22512317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newlands |
E556550
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Claremont |
—
|
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: Claremont | Statement: [Newlands, adjacentTo, Claremont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claremont Context triple: [Newlands, adjacentTo, Claremont]
-
A.
Claremont
Claremont is a residential area within the City of Salford in Greater Manchester, England.
-
B.
Claremont
Claremont is a small town located in the rural interior of Saint Ann Parish on Jamaica’s north coast.
-
C.
Claremont
Claremont is a historic country house and estate in Surrey, England, known for its landscaped gardens and royal connections.
-
D.
Claremont
Claremont is a small, affluent college town in eastern Los Angeles County, California, known for its consortium of higher education institutions collectively called the Claremont Colleges.
-
E.
Claremont
chosen
Claremont is a well-established residential and commercial suburb in Cape Town, South Africa, known for its shopping centers, schools, and proximity to the University of Cape Town.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d61a27881909faed490d2b65f39 |
completed | April 29, 2026, 1:22 a.m. |
Created at: April 16, 2026, 8:50 p.m.