Triple
T4229175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Mostar |
E94534
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Mostar |
E94534
|
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: Mostar | Statement: [University of Mostar, locatedIn, Mostar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mostar Context triple: [University of Mostar, locatedIn, Mostar]
-
A.
Mostar
chosen
Mostar is a historic city in Bosnia and Herzegovina, best known for its iconic Ottoman-era Stari Most (Old Bridge) spanning the Neretva River.
-
B.
Mostar Canton
Mostar Canton is an administrative region in Bosnia and Herzegovina that encompasses the city of Mostar and its surrounding area.
-
C.
Jajce
Jajce is a historic town in central Bosnia and Herzegovina known for its medieval fortress, picturesque waterfall, and key role in World War II as a political center of the Yugoslav resistance.
-
D.
Stari Grad
Stari Grad is the historic central municipality of Belgrade, known for its old town architecture, cultural landmarks, and key administrative and commercial areas.
-
E.
Niš
Niš is one of the largest and oldest cities in Serbia, known as a key cultural, economic, and transportation hub in the southern part of the country.
- 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e61ccc081909b880baf1d6a0f24 |
completed | March 12, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d05f55f48190b671830e173ef2ba |
completed | March 14, 2026, 9:17 p.m. |
Created at: March 12, 2026, 11:05 p.m.