Triple
T12557524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jabez Olssen |
E295255
|
entity |
| Predicate | basedIn |
P40
|
FINISHED |
| Object | Wellington |
E18156
|
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: Wellington | Statement: [Jabez Olssen, basedIn, Wellington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wellington Context triple: [Jabez Olssen, basedIn, Wellington]
-
A.
Wellington
Wellington is a regional town in New South Wales, Australia, known for its agricultural surroundings and location near the junction of the Macquarie and Bell rivers.
-
B.
Wellington
Wellington is a Chicago Transit Authority 'L' station on the Brown Line located in the Lakeview neighborhood of Chicago, Illinois.
-
C.
Wellington
chosen
Wellington is the compact, hilly coastal city at the southern tip of New Zealand’s North Island known for its vibrant arts scene, windy climate, and role as the country’s political and cultural hub.
-
D.
Wellington
Wellington is a small village in Lorain County, Ohio, known for its historic downtown and rural Midwestern character.
-
E.
Wellington
Wellington is a historic South African town in the Western Cape known for its wine, fruit farming, and scenic position at the foot of the Groenberg mountains.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95491d9688190a6b88a939124233e |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6555c73208190a8846a5db1a6802e |
completed | May 2, 2026, 7:49 p.m. |
Created at: April 8, 2026, 11:47 p.m.