Triple
T6048173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tore |
E134719
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Tore (with diacritics or regional spellings) |
E134719
|
NE FINISHED |
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: Tore (with diacritics or regional spellings) | Statement: [Tore, hasVariant, Tore (with diacritics or regional spellings)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tore (with diacritics or regional spellings) Context triple: [Tore, hasVariant, Tore (with diacritics or regional spellings)]
-
A.
Tore
chosen
Tore is a Scandinavian masculine given name commonly used in Norway and other Nordic countries.
-
B.
Torez
Torez is a town in eastern Ukraine’s Donetsk region, internationally known as the nearby area where Malaysia Airlines Flight 17 was shot down in 2014.
-
C.
Toulonnais
Toulonnais is the French term for a person or thing originating from the Mediterranean port city of Toulon in southeastern France.
-
D.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
E.
Turek
Turek is a town in central Poland known historically for its textile industry and its location in the Greater Poland region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056f387cc8190920b846995761aec |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c113a65164819090883dbad3be5026 |
completed | March 23, 2026, 10:19 a.m. |
Created at: March 22, 2026, 4:09 p.m.