Triple
T19576830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Stewart |
E489877
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Aberdeen |
—
|
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: Aberdeen | Statement: [Kevin Stewart, residence, Aberdeen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aberdeen Context triple: [Kevin Stewart, residence, Aberdeen]
-
A.
Aberdeen
chosen
Aberdeen is a major port city in northeast Scotland known for its North Sea oil industry, granite architecture, and role as a regional economic and cultural hub.
-
B.
Aberdeen
Aberdeen is a small rural town in the Upper Hunter region of New South Wales, Australia, known historically for its agricultural and meat-processing industries.
-
C.
Aberdeen
Aberdeen is a residential neighbourhood in the city of Kamloops, British Columbia, known for its hillside location, views over the valley, and mix of family homes and commercial amenities.
-
D.
Aberdeen
Aberdeen is a small city in northeastern South Dakota known as a regional hub for agriculture, education, and rail transport.
-
E.
Aberdeen
Aberdeen is a coastal town on the southwest side of Hong Kong Island known for its traditional fishing community and famous floating village and seafood restaurants.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e64024c5b08190bbff6df633857874 |
completed | April 20, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:42 p.m.