Triple

T17133670
Position Surface form Disambiguated ID Type / Status
Subject Ranko Matasović E415781 entity
Predicate workLocation P7 FINISHED
Object Zagreb E31635 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: Zagreb | Statement: [Ranko Matasović, workLocation, Zagreb]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zagreb
Context triple: [Ranko Matasović, workLocation, Zagreb]
  • A. Zagreb chosen
    Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
  • B. Osijek
    Osijek is a prominent city in eastern Croatia known as an economic, cultural, and educational center of the Slavonia region.
  • C. Karlovac
    Karlovac is a historic Croatian city strategically located at the confluence of four rivers, known for its star-shaped Renaissance fortress and role as a key military and trading center.
  • D. Sarajevo
    Sarajevo is the capital and largest city of Bosnia and Herzegovina, historically known as the site of Archduke Franz Ferdinand’s assassination that sparked World War I.
  • E. Rijeka
    Rijeka is a significant Croatian port city on the Adriatic Sea, known for its maritime industry, cultural heritage, and role as a key transport hub.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f02cbb7881908aa69c3443d149d5 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01414eca3c8190aeec22fab3b5e767 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:36 a.m.