Triple
T16749984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beograđanka |
E407046
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Terazije |
E560498
|
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: Terazije | Statement: [Beograđanka, locatedNear, Terazije]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terazije Context triple: [Beograđanka, locatedNear, Terazije]
-
A.
Terazije
chosen
Terazije is a central and historic square in Belgrade, Serbia, known as a major commercial, cultural, and transport hub of the city.
-
B.
Surdulica
Surdulica is a small town and municipality in southern Serbia known for its mountainous surroundings and role as a local administrative and economic center.
-
C.
Jérica
Jérica is a historic municipality in the province of Castellón, in Spain’s Valencian Community, known for its medieval architecture and prominent Mudejar-style bell tower.
-
D.
Dajan
Dajan is a variant transliteration of the name Dayan, which is used in various cultural and linguistic contexts.
-
E.
Čukarica
Čukarica is a municipality of Belgrade known for its mix of urban neighborhoods, industrial zones, and green areas along the Sava River.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa265a908190a87fa4612bfe6396 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a522255c8190ab16d7ad233fcd3b |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.