Triple
T5992120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liepāja |
E133373
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Jaunliepāja
Jaunliepāja is a district of the Latvian port city of Liepāja, known for its mix of residential areas and industrial heritage near the Baltic Sea coast.
|
E562335
|
NE FINISHED |
How this triple was built (4 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: Jaunliepāja | Statement: [Liepāja, hasDistrict, Jaunliepāja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jaunliepāja Context triple: [Liepāja, hasDistrict, Jaunliepāja]
-
A.
Jekabpils
Jekabpils is a town in southeastern Latvia known for its historic architecture and scenic location along the Daugava River.
-
B.
Jaunsari
Jaunsari is an Indo-Aryan language spoken by the Jaunsari people in the Jaunsar-Bawar region of northern India.
-
C.
Jelgava
Jelgava is a city in central Latvia known for its historic Jelgava Palace and role as a regional cultural and educational center.
-
D.
Kalnciems
Kalnciems is a settlement in present-day Latvia historically associated with the Baltic German nobility, including the birth of Ernst Johann von Biron, Duke of Courland.
-
E.
Kuldīga
Kuldīga is a historic town in western Latvia known for its well-preserved old town and proximity to the Venta Rapid, one of Europe’s widest natural waterfalls.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jaunliepāja Triple: [Liepāja, hasDistrict, Jaunliepāja]
Generated description
Jaunliepāja is a district of the Latvian port city of Liepāja, known for its mix of residential areas and industrial heritage near the Baltic Sea coast.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jaunliepāja Target entity description: Jaunliepāja is a district of the Latvian port city of Liepāja, known for its mix of residential areas and industrial heritage near the Baltic Sea coast.
-
A.
Jekabpils
Jekabpils is a town in southeastern Latvia known for its historic architecture and scenic location along the Daugava River.
-
B.
Jaunsari
Jaunsari is an Indo-Aryan language spoken by the Jaunsari people in the Jaunsar-Bawar region of northern India.
-
C.
Jelgava
Jelgava is a city in central Latvia known for its historic Jelgava Palace and role as a regional cultural and educational center.
-
D.
Kalnciems
Kalnciems is a settlement in present-day Latvia historically associated with the Baltic German nobility, including the birth of Ernst Johann von Biron, Duke of Courland.
-
E.
Kuldīga
Kuldīga is a historic town in western Latvia known for its well-preserved old town and proximity to the Venta Rapid, one of Europe’s widest natural waterfalls.
- F. None of above. chosen
Provenance (5 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04e8fd030819095a4f3b3d425ec21 |
completed | March 22, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c10861c0bc8190b6290d7363f4264a |
completed | March 23, 2026, 9:31 a.m. |
| NEDg | Description generation | batch_69c10c44b6408190be8bc1d96e0db2e4 |
completed | March 23, 2026, 9:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c10cd7c1c8819085ec8bee7f42afc4 |
completed | March 23, 2026, 9:50 a.m. |
Created at: March 22, 2026, 4:05 p.m.