Triple
T17614427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Żagań |
E429045
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Netphen |
—
|
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: Netphen | Statement: [Żagań, hasTwinTown, Netphen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Netphen Context triple: [Żagań, hasTwinTown, Netphen]
-
A.
Netphen
chosen
Netphen is a small town in the Siegerland region of North Rhine-Westphalia, Germany, known for its surrounding forests and role as a local administrative and economic center.
-
B.
Netze
Netze is the German name for the Noteć, a river in north-central Poland that is a tributary of the Warta.
-
C.
Netia
Netia is one of Poland’s leading telecommunications providers, offering broadband internet and related services to residential and business customers nationwide.
-
D.
Phene
Phene is a character in Robert Browning's verse drama "Pippa Passes," depicted as a young woman whose life is profoundly affected by the innocent songs of the protagonist, Pippa.
-
E.
Nynetjer
Nynetjer was an early Egyptian pharaoh of the Second Dynasty, known from archaeological and inscriptional evidence as a ruler during the formative period of the ancient Egyptian state.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2fd96481908c9f3b566fca6907 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 5:51 a.m.