Triple
T3270598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Prussia |
E68636
|
entity |
| Predicate | containedCity |
P8465
|
FINISHED |
| Object | Elbing |
E226489
|
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: Elbing | Statement: [West Prussia, containedCity, Elbing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elbing Context triple: [West Prussia, containedCity, Elbing]
-
A.
Elbing
chosen
Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
-
B.
Babruysk
Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
-
C.
Vitebsk
Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
-
D.
Orsha
Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
-
E.
Lichtenrade
Lichtenrade is a southern residential locality of Berlin known for its village-like character, green spaces, and proximity to the city’s outskirts.
- 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adaff349148190beae8c0994b7ad83 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b31a698ab08190b558c4ff3f9b27fc |
completed | March 12, 2026, 7:56 p.m. |
Created at: March 8, 2026, 3:09 p.m.