Triple
T18318837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Lane |
E438816
|
entity |
| Predicate | sire |
P25213
|
FINISHED |
| Object | Frankel |
—
|
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: Frankel | Statement: [Hurricane Lane, sire, Frankel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frankel Context triple: [Hurricane Lane, sire, Frankel]
-
A.
Frankel
Frankel is the birth surname of American actress and comedian Bea Arthur, best known for her roles in the television series "Maude" and "The Golden Girls."
-
B.
Frankel
chosen
Frankel is a legendary, unbeaten British Thoroughbred racehorse widely regarded as one of the greatest racehorses of all time.
-
C.
Danehill
Danehill was a champion Irish-bred Thoroughbred racehorse who became one of the most influential and successful stallions in modern breeding history.
-
D.
Northern Dancer
Northern Dancer was a legendary Canadian-bred Thoroughbred racehorse and stallion whose exceptional success as a sire made him one of the most influential bloodlines in modern horse racing and breeding.
-
E.
Dr. Fager
Dr. Fager was a legendary American Thoroughbred racehorse renowned for his speed, versatility, and multiple championship titles in the late 1960s.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aa342a881909afcd995405027af |
completed | April 19, 2026, 5:02 p.m. |
Created at: April 10, 2026, 10:36 a.m.