Triple
T3840233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waterloo |
E93431
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Lasne |
E189049
|
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: Lasne | Statement: [Waterloo, nearbyCity, Lasne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lasne Context triple: [Waterloo, nearbyCity, Lasne]
-
A.
Lasne
chosen
Lasne is a picturesque, affluent municipality in Walloon Brabant, Belgium, known for its rural character and high quality of life.
-
B.
Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
-
C.
Hańska
Hańska is a Polish surname most notably associated with Ewelina Hańska, the Polish noblewoman and later wife of French novelist Honoré de Balzac.
-
D.
Kovel
Kovel is a historic town in northwestern Ukraine, located in the Volyn region and known as a former important railway and trade hub.
-
E.
Svetogorsk
Svetogorsk is a small industrial town in northwestern Russia near the Finnish border, known for its paper mill and location along the Vuoksi River.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeeba1535c8190b36e2ab2d4514b54 |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5040a8b808190874ad1a5152adf1f |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:18 p.m.