Triple
T7974638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drohobych |
E185412
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Nysa |
E613308
|
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: Nysa | Statement: [Drohobych, twinTown, Nysa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nysa Context triple: [Drohobych, twinTown, Nysa]
-
A.
Nysa
Nysa is a mythical mountainous region in Greek mythology, often associated with the upbringing of the god Dionysus.
-
B.
Nysa
chosen
Nysa is a historic town in southwestern Poland known for its well-preserved old town, religious architecture, and role as a former important Silesian trade and cultural center.
-
C.
Nysa Kłodzka
Nysa Kłodzka is a river in southwestern Poland that flows through the Kłodzko Valley and Silesia before joining the Oder.
-
D.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
-
E.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
- 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bf42a508190bb661fce34ec0151 |
completed | March 31, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0bb089881909d3ec17a3330ce25 |
completed | March 31, 2026, 2:56 p.m. |
Created at: March 30, 2026, 5:14 p.m.