Triple
T18085725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terence (given name) |
E432827
|
entity |
| Predicate | hasAlternativeSpelling |
P457
|
FINISHED |
| Object | Terance |
—
|
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: Terance | Statement: [Terence (given name), hasAlternativeSpelling, Terance]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terance Context triple: [Terence (given name), hasAlternativeSpelling, Terance]
-
A.
Terance
chosen
Terance is the first name of Terance Mann, an American professional basketball player in the NBA.
-
B.
Terrance
Terrance is the given first name of Terry Sawchuk, the legendary Canadian Hall of Fame NHL goaltender.
-
C.
Terrance
Terrance is the given name of Terrance Dicks, a British writer best known for his work on the television series Doctor Who and its novelizations.
-
D.
Terrance
Terrance is the given first name of Terry Fox, the Canadian athlete and cancer research activist renowned for his Marathon of Hope.
-
E.
Treveris
Treveris is the historical city now known as Trier, one of the oldest cities in Germany and a major center of the Roman Empire in the region.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9fdb00c8190b4769699e94c8941 |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:27 a.m.