Triple

T4502916
Position Surface form Disambiguated ID Type / Status
Subject Ertuğrul E101264 entity
Predicate honorific P301 FINISHED
Object Gazi E98410 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: Gazi | Statement: [Ertuğrul, honorific, Gazi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gazi
Context triple: [Ertuğrul, honorific, Gazi]
  • A. Gazi chosen
    Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
  • B. Ziya
    Ziya is a masculine given name of Turkish origin, historically associated with notable figures such as sociologist and nationalist thinker Ziya Gökalp.
  • C. Ahmet
    Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
  • D. Seyhun
    Seyhun is the historical name used in Islamic and Central Asian sources for the Syr Darya River, one of the major rivers of Central Asia.
  • E. Gökalp
    Gökalp is a Turkish surname most prominently associated with Ziya Gökalp, an influential early 20th-century sociologist, writer, and ideologue of Turkish nationalism.
  • 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_69bd43d175248190894dc58b5b395c26 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd56fb2bec8190b74b6a49d9475514 completed March 20, 2026, 2:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6f90d6a4819085d911de5443f111 completed March 20, 2026, 4:02 p.m.
Created at: March 20, 2026, 1:01 p.m.