Triple
T22069736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebilj fountain |
E545372
|
entity |
| Predicate | hasNameInLocalLanguage |
P21937
|
FINISHED |
| Object |
Sebilj
Sebilj is a historic Ottoman-style wooden fountain and one of the most recognizable landmarks in Sarajevo, Bosnia and Herzegovina.
|
E1517475
|
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: Sebilj | Statement: [Sebilj fountain, hasNameInLocalLanguage, Sebilj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sebilj Context triple: [Sebilj fountain, hasNameInLocalLanguage, Sebilj]
-
A.
Bileća
Bileća is a small town and municipality in southeastern Bosnia and Herzegovina, known for its nearby artificial lake and karst landscape.
-
B.
Pilica
Pilica is a town in southern Poland known for its historic architecture and proximity to medieval Smoleń Castle.
-
C.
Bjelolasica
Bjelolasica is a prominent mountain peak in Croatia known for its forested slopes and former ski facilities.
-
D.
Dajla
Dajla is an alternative name for Dakhla, a coastal city in Western Sahara known for its fishing industry and popular kitesurfing spots.
-
E.
Žepa
Žepa is a small town in eastern Bosnia and Herzegovina that became known as a UN-declared "safe area" and site of a tragic episode during the Bosnian War.
- 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: Sebilj Triple: [Sebilj fountain, hasNameInLocalLanguage, Sebilj]
Generated description
Sebilj is a historic Ottoman-style wooden fountain and one of the most recognizable landmarks in Sarajevo, Bosnia and Herzegovina.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sebilj Target entity description: Sebilj is a historic Ottoman-style wooden fountain and one of the most recognizable landmarks in Sarajevo, Bosnia and Herzegovina.
-
A.
Bileća
Bileća is a small town and municipality in southeastern Bosnia and Herzegovina, known for its nearby artificial lake and karst landscape.
-
B.
Pilica
Pilica is a town in southern Poland known for its historic architecture and proximity to medieval Smoleń Castle.
-
C.
Bjelolasica
Bjelolasica is a prominent mountain peak in Croatia known for its forested slopes and former ski facilities.
-
D.
Dajla
Dajla is an alternative name for Dakhla, a coastal city in Western Sahara known for its fishing industry and popular kitesurfing spots.
-
E.
Žepa
Žepa is a small town in eastern Bosnia and Herzegovina that became known as a UN-declared "safe area" and site of a tragic episode during the Bosnian War.
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1288724e881908b38fe7e56d3b448 |
completed | April 28, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a80b378888190b7d26cd57a6eec23 |
completed | May 18, 2026, 3 a.m. |
| NEDg | Description generation | batch_6a0a817450ac81908479592e5cfc0126 |
completed | May 18, 2026, 3:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a827806a8819099933d597773a1e1 |
completed | May 18, 2026, 3:07 a.m. |
Created at: April 16, 2026, 8:28 p.m.