Triple

T23758560
Position Surface form Disambiguated ID Type / Status
Subject Söğüt principality of Ertuğrul E587185 entity
Predicate militaryRole P9463 FINISHED
Object gazi frontier beylik
The gazi frontier beylik was a small, militarized Turkish border principality devoted to holy war and territorial expansion against neighboring non-Muslim states in Anatolia and the Balkans.
E163248 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 frontier beylik | Statement: [Söğüt principality of Ertuğrul, militaryRole, gazi frontier beylik]
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: gazi frontier beylik
Triple: [Söğüt principality of Ertuğrul, militaryRole, gazi frontier beylik]
Generated description
The gazi frontier beylik was a small, militarized Turkish border principality devoted to holy war and territorial expansion against neighboring non-Muslim states in Anatolia and the Balkans.

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_69e2490a0eec81908cdef8a862828d7a completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bdaf52848190b034208de4c4e01a completed April 29, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53da0d6081909c98a3b6496f5914 completed May 21, 2026, 6:50 p.m.
NEDg Description generation batch_6a0f5558f50c8190a268fbcde798512e completed May 21, 2026, 6:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f56691aa08190b46a9ad2c3dce1d0 completed May 21, 2026, 7 p.m.
Created at: April 17, 2026, 7:14 p.m.