Triple
T19344561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ogden Nash |
E483841
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ogden Nash |
—
|
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: Ogden Nash | Statement: [Ogden Nash, name, Ogden Nash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ogden Nash Context triple: [Ogden Nash, name, Ogden Nash]
-
A.
Ogden Nash
chosen
Ogden Nash was an American poet celebrated for his light verse, playful rhymes, and witty observations on everyday life.
-
B.
Gary Troup
Gary Troup is a fictional New Zealand cricketer and author from the TV series "Lost," known for writing the in-universe book "Bad Twin."
-
C.
G. G. Berry
G. G. Berry was a British logician and mathematician best known for formulating the Berry paradox, an influential semantic paradox in the foundations of mathematics and logic.
-
D.
Archy McNally
Archy McNally is a charming, witty playboy sleuth who stars as the unconventional private investigator in Lawrence Sanders’ popular McNally mystery novels set in Palm Beach.
-
E.
Cecil Layendecker
Cecil Layendecker is a relatively obscure individual known primarily by name, with no widely documented public achievements or biographical details.
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e618598dc08190a723398dd6fe551d |
completed | April 20, 2026, 12:13 p.m. |
Created at: April 10, 2026, 1:34 p.m.