Triple
T8576933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MV Puyallup |
E203069
|
entity |
| Predicate | class |
P87
|
FINISHED |
| Object | Jumbo Mark II |
E736744
|
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: Jumbo Mark II | Statement: [MV Puyallup, class, Jumbo Mark II]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jumbo Mark II Context triple: [MV Puyallup, class, Jumbo Mark II]
-
A.
Jumbo Mark II
chosen
Jumbo Mark II is a class of large, modern car ferries operated by Washington State Ferries for high-capacity passenger and vehicle transport.
-
B.
Jumbo
Jumbo was the nickname of British Army officer Field Marshal Henry Maitland Wilson, a senior commander during the Second World War.
-
C.
Jumbo
Jumbo is a 1935 Rodgers and Hart Broadway musical comedy best known for its circus setting and elaborate live-animal performances.
-
D.
Jumbo
Jumbo is a prominent mountain peak in New Zealand’s Tararua Range, popular with trampers for its alpine views and access to nearby huts and ridgelines.
-
E.
Jumbo
Jumbo is a major Latin American supermarket and hypermarket chain known for offering a wide range of groceries and household products.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea97787481909ebbaa45f59cbdaa |
completed | March 31, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce899dd7d48190b44338b92ad68bd0 |
completed | April 2, 2026, 3:22 p.m. |
Created at: March 30, 2026, 6:21 p.m.