Triple

T9611848
Position Surface form Disambiguated ID Type / Status
Subject Saint Thaddeus Monastery E232119 entity
Predicate locatedNear P294 FINISHED
Object Chaldoran
Chaldoran is a district in Iran’s West Azerbaijan Province, known for its historical significance and proximity to important religious and cultural sites.
E810940 NE FINISHED

How this triple was built (4 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: Chaldoran | Statement: [Saint Thaddeus Monastery, locatedNear, Chaldoran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chaldoran
Context triple: [Saint Thaddeus Monastery, locatedNear, Chaldoran]
  • A. Tynaarlo
    Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
  • B. Terrigal
    Terrigal is a popular coastal town in New South Wales, Australia, known for its surf beaches, scenic headlands, and vibrant holiday atmosphere.
  • C. Rehling
    Rehling is a small municipality in the Bavarian region of Swabia in southern Germany.
  • D. Chandor
    Chandor is the surname of American filmmaker J. C. Chandor, known for directing films such as "Margin Call" and "A Most Violent Year."
  • E. Tanneron
    Tanneron is a commune in southeastern France’s Var department, known for its hilly landscapes and extensive mimosa forests overlooking the Mediterranean hinterland.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Chaldoran
Triple: [Saint Thaddeus Monastery, locatedNear, Chaldoran]
Generated description
Chaldoran is a district in Iran’s West Azerbaijan Province, known for its historical significance and proximity to important religious and cultural sites.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Chaldoran
Target entity description: Chaldoran is a district in Iran’s West Azerbaijan Province, known for its historical significance and proximity to important religious and cultural sites.
  • A. Tynaarlo
    Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
  • B. Terrigal
    Terrigal is a popular coastal town in New South Wales, Australia, known for its surf beaches, scenic headlands, and vibrant holiday atmosphere.
  • C. Rehling
    Rehling is a small municipality in the Bavarian region of Swabia in southern Germany.
  • D. Chandor
    Chandor is the surname of American filmmaker J. C. Chandor, known for directing films such as "Margin Call" and "A Most Violent Year."
  • E. Tanneron
    Tanneron is a commune in southeastern France’s Var department, known for its hilly landscapes and extensive mimosa forests overlooking the Mediterranean hinterland.
  • F. None of above. chosen

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_69ca8485a90c819094fe40b42fde9d70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a87764481909ab96cd2ab96d14b completed April 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d179513f9081909bcd9a456c640ba3 completed April 4, 2026, 8:49 p.m.
NEDg Description generation batch_69d17b87ec6c8190a265bdbb6855dca5 completed April 4, 2026, 8:58 p.m.
NED2 Entity disambiguation (via description) batch_69d17beebd748190b85d7bd549276197 completed April 4, 2026, 9 p.m.
Created at: March 30, 2026, 8:09 p.m.