Triple
T21947996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrell |
E541983
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Harell |
—
|
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: Harell | Statement: [Harrell, hasVariantSpelling, Harell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harell Context triple: [Harrell, hasVariantSpelling, Harell]
-
A.
Harrie
Harrie is a given name, typically a variant spelling of Harry, used for both males and females in various countries.
-
B.
Harnell
Harnell is a surname most notably associated with American voice actor and singer Jess Harnell.
-
C.
Harrelle
chosen
Harrelle is a less common variant of the English surname Harrell, typically of Anglo-Saxon origin.
-
D.
Harron
Harron is a surname most notably associated with early 20th-century American silent film actor Robert Harron.
-
E.
Hannen
Hannen is an English surname associated with several notable figures, including actors and judges, in British history.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243a2f788190bd4625fa79888696 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:57 p.m.