Triple
T22974673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claude Pepper Memorial Highway (Florida) |
E571280
|
entity |
| Predicate | commemorates |
P501
|
FINISHED |
| Object | Claude Pepper |
—
|
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: Claude Pepper | Statement: [Claude Pepper Memorial Highway (Florida), commemorates, Claude Pepper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claude Pepper Context triple: [Claude Pepper Memorial Highway (Florida), commemorates, Claude Pepper]
-
A.
Claude Pepper
chosen
Claude Pepper was a long-serving American politician from Florida known for his advocacy of New Deal policies, social welfare programs, and the rights of the elderly.
-
B.
Howard E. Smith
Howard E. Smith is a film editor best known for his work on the acclaimed drama "Glengarry Glen Ross."
-
C.
Howard E. Smith
Howard E. Smith is a film editor best known for his work on the thriller "Snakes on a Plane."
-
D.
Howard E. Smith
Howard E. Smith is a film editor best known for his work on major Hollywood productions, including the action thriller "Point Break."
-
E.
Howard E. Smith
Howard E. Smith is a film editor best known for his work on genre films such as the cult vampire movie "Near Dark."
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18235de508190ab9675d005870ff6 |
completed | April 29, 2026, 3:59 a.m. |
Created at: April 17, 2026, 3:48 p.m.