Triple
T21891562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerrick Harding |
E540560
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Harding |
—
|
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: Harding | Statement: [Jerrick Harding, hasFamilyName, Harding]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harding Context triple: [Jerrick Harding, hasFamilyName, Harding]
-
A.
Harding
chosen
Harding is the surname of Warren G. Harding, the 29th president of the United States who served from 1921 to 1923.
-
B.
The Hayes
The Hayes is a prominent pedestrianised shopping street and public thoroughfare in the centre of Cardiff, Wales.
-
C.
Ben Harrison
Ben Harrison is a central character in the 1998 family drama film "Stepmom," which explores the emotional challenges of divorce, illness, and blended families.
-
D.
Marriner
Marriner is the given name of Marriner S. Eccles, a prominent American banker and former chairman of the U.S. Federal Reserve.
-
E.
Coolidge
Coolidge is an American actress and comedian best known for her roles in films like "Legally Blonde" and "American Pie" and the TV series "The White Lotus."
- 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_69e0c47a95908190ae3e19b716accb3d |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fc3727c8190b4d5d5a44aa2e55e |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:06 p.m.