Triple
T5335593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarajevo Canton |
E123817
|
entity |
| Predicate | hasMountain |
P10602
|
FINISHED |
| Object |
Igman
Igman is a mountain in central Bosnia and Herzegovina known for its forests, ski facilities, and role as a key venue during the 1984 Winter Olympics near Sarajevo.
|
E512953
|
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: Igman | Statement: [Sarajevo Canton, hasMountain, Igman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Igman Context triple: [Sarajevo Canton, hasMountain, Igman]
-
A.
Oreshak
Oreshak is a village in central Bulgaria known for its proximity to the historic Troyan Monastery and its traditional crafts and cultural heritage.
-
B.
Stryama
Stryama is a river in Bulgaria that flows through the central part of the country before joining the Maritsa River.
-
C.
Taborio
Taborio is a village settlement located on the island of Nonouti in the Republic of Kiribati.
-
D.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
-
E.
Kameçvara
Kameçvara was a prominent king of the medieval Javanese Kediri Kingdom, remembered for his prosperous reign and association with the classic romance tale of Panji.
- 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: Igman Triple: [Sarajevo Canton, hasMountain, Igman]
Generated description
Igman is a mountain in central Bosnia and Herzegovina known for its forests, ski facilities, and role as a key venue during the 1984 Winter Olympics near Sarajevo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Igman Target entity description: Igman is a mountain in central Bosnia and Herzegovina known for its forests, ski facilities, and role as a key venue during the 1984 Winter Olympics near Sarajevo.
-
A.
Oreshak
Oreshak is a village in central Bulgaria known for its proximity to the historic Troyan Monastery and its traditional crafts and cultural heritage.
-
B.
Stryama
Stryama is a river in Bulgaria that flows through the central part of the country before joining the Maritsa River.
-
C.
Taborio
Taborio is a village settlement located on the island of Nonouti in the Republic of Kiribati.
-
D.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
-
E.
Kameçvara
Kameçvara was a prominent king of the medieval Javanese Kediri Kingdom, remembered for his prosperous reign and association with the classic romance tale of Panji.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85af799081909ee60bfbb65149ee |
completed | March 20, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18be4bb88190a2b83e51716e677e |
completed | March 21, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_69bf194c53a48190b0895bbe9aa2f6f1 |
completed | March 21, 2026, 10:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf1a198418819089b25102733f9191 |
completed | March 21, 2026, 10:22 p.m. |
Created at: March 20, 2026, 2 p.m.