Triple
T14629183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodgers and Hart |
E343433
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Jumbo |
E333806
|
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 | Statement: [Rodgers and Hart, notableWork, Jumbo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jumbo Context triple: [Rodgers and Hart, notableWork, Jumbo]
-
A.
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.
-
B.
Jumbo
Jumbo is a major Latin American supermarket and hypermarket chain known for offering a wide range of groceries and household products.
-
C.
Jumbo
Jumbo is a prominent historic water tower in Colchester, England, renowned for its massive size and distinctive Victorian brick architecture.
-
D.
Jumbo
Jumbo was the nickname of British Army officer Field Marshal Henry Maitland Wilson, a senior commander during the Second World War.
-
E.
Jumbo
chosen
Jumbo is a 1935 Rodgers and Hart Broadway musical comedy best known for its circus setting and elaborate live-animal performances.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4a7c8fc81909d10c1f563d7d1e7 |
completed | April 14, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda92ded848190b031d3ff29e54a00 |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 10, 2026, 1:26 a.m.