Triple
T1985509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tartu |
E43129
|
entity |
| Predicate | historicalName |
P65
|
FINISHED |
| Object |
Jurjev
Jurjev is a historical name for the Estonian city of Tartu, reflecting its past under various regional powers.
|
E222922
|
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: Jurjev | Statement: [Tartu, historicalName, Jurjev]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jurjev Context triple: [Tartu, historicalName, Jurjev]
-
A.
Lazarevac
Lazarevac is a suburban municipality of Belgrade in central Serbia, known for its coal mining industry and the Kolubara coal basin.
-
B.
Smiljan
Smiljan is a village in modern-day Croatia best known as the birthplace of inventor Nikola Tesla.
-
C.
Crnogorci
Crnogorci are a South Slavic ethnic group primarily associated with the country of Montenegro, known for their distinct cultural and historical identity in the Balkans.
-
D.
Baščaršija
Baščaršija is Sarajevo’s historic Ottoman-era bazaar and cultural center, known for its narrow cobbled streets, traditional shops, and iconic architecture.
-
E.
Rakovica
Rakovica is a suburban municipality of Belgrade, Serbia, known for its mixed residential and industrial areas and proximity to forested landscapes.
- 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: Jurjev Triple: [Tartu, historicalName, Jurjev]
Generated description
Jurjev is a historical name for the Estonian city of Tartu, reflecting its past under various regional powers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jurjev Target entity description: Jurjev is a historical name for the Estonian city of Tartu, reflecting its past under various regional powers.
-
A.
Lazarevac
Lazarevac is a suburban municipality of Belgrade in central Serbia, known for its coal mining industry and the Kolubara coal basin.
-
B.
Smiljan
Smiljan is a village in modern-day Croatia best known as the birthplace of inventor Nikola Tesla.
-
C.
Crnogorci
Crnogorci are a South Slavic ethnic group primarily associated with the country of Montenegro, known for their distinct cultural and historical identity in the Balkans.
-
D.
Baščaršija
Baščaršija is Sarajevo’s historic Ottoman-era bazaar and cultural center, known for its narrow cobbled streets, traditional shops, and iconic architecture.
-
E.
Rakovica
Rakovica is a suburban municipality of Belgrade, Serbia, known for its mixed residential and industrial areas and proximity to forested landscapes.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb821c2d48190abea6c89f37b51b1 |
completed | March 7, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0331eec881909463163fb71e4eba |
completed | March 8, 2026, 11:16 p.m. |
| NEDg | Description generation | batch_69ae03e575a88190a93181eb9d9bc3eb |
completed | March 8, 2026, 11:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0473aecc8190b3da07fb8fd18e81 |
completed | March 8, 2026, 11:21 p.m. |
Created at: March 4, 2026, 7:37 p.m.