Triple

T38335512
Position Surface form Disambiguated ID Type / Status
Subject Ostrog Monastery E1037944 entity
Predicate locatedIn P40 FINISHED
Object Danilovgrad Municipality
Danilovgrad Municipality is a central Montenegrin municipality known for encompassing the famous Orthodox pilgrimage site of Ostrog Monastery.
E2266746 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: Danilovgrad Municipality | Statement: [Ostrog Monastery, locatedIn, Danilovgrad Municipality]
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: Danilovgrad Municipality
Triple: [Ostrog Monastery, locatedIn, Danilovgrad Municipality]
Generated description
Danilovgrad Municipality is a central Montenegrin municipality known for encompassing the famous Orthodox pilgrimage site of Ostrog Monastery.

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_69f76e20d65c81909619ac0dd85c56f0 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc6bad1a081909a57e8f19c249dcb completed May 7, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41a7ecbe84819087dddac5370e5e2b completed June 28, 2026, 11:02 p.m.
NEDg Description generation batch_6a41abf6e6c88190903eeb75fd3dc905 completed June 28, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_6a41ac5d1fa881908faedb41784d3d3d completed June 28, 2026, 11:21 p.m.
Created at: May 3, 2026, 4:30 p.m.