Triple
T21521024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Potter |
E530974
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Potter |
—
|
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: Potter | Statement: [Tommy Potter, familyName, Potter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Potter Context triple: [Tommy Potter, familyName, Potter]
-
A.
Potter
chosen
Potter is the surname of Beatrix Potter, the renowned English writer, illustrator, and natural scientist best known for her children's books featuring animal characters such as Peter Rabbit.
-
B.
Potter
Potter is a masculine given name most notably borne by U.S. Supreme Court Justice Potter Stewart.
-
C.
Potter
Potter is a small town located in Yates County in the Finger Lakes region of New York State.
-
D.
de Potter
de Potter is a Belgian noble family name historically associated with political and intellectual figures such as Louis de Potter.
-
E.
Harry Potter
Harry Potter is a young wizard who attends Hogwarts School of Witchcraft and Wizardry and becomes famous for surviving an attack by the dark wizard Lord Voldemort.
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee884bfa548190a39e5992ed6bb8a8 |
completed | April 26, 2026, 9:49 p.m. |
Created at: April 16, 2026, 6:26 p.m.