Triple

T16417988
Position Surface form Disambiguated ID Type / Status
Subject Province of South Sardinia E398737 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Ussassai
Ussassai is a small rural municipality in Sardinia, Italy, known for its mountainous landscape and traditional Sardinian culture.
E1211172 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: Ussassai | Statement: [Province of South Sardinia, containsAdministrativeTerritorialEntity, Ussassai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ussassai
Context triple: [Province of South Sardinia, containsAdministrativeTerritorialEntity, Ussassai]
  • A. Rascia
    Rascia is a historical region in the central Balkans that formed the medieval core of the Serbian state.
  • B. Urusemal
    Urusemal is a surname most notably associated with Joseph J. Urusemal, a politician from the Federated States of Micronesia who served as its president.
  • C. Yussois
    Yussois is the French demonym for inhabitants of the town of Yutz in northeastern France.
  • D. Oruzgan
    Oruzgan is a central Afghan province known for its mountainous terrain, tribal Pashtun population, and strategic role in recent conflicts.
  • E. Ussat
    Ussat is a small commune in the Ariège department of southwestern France, located in the Pyrenees and known for its proximity to notable caves and thermal springs.
  • 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: Ussassai
Triple: [Province of South Sardinia, containsAdministrativeTerritorialEntity, Ussassai]
Generated description
Ussassai is a small rural municipality in Sardinia, Italy, known for its mountainous landscape and traditional Sardinian culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ussassai
Target entity description: Ussassai is a small rural municipality in Sardinia, Italy, known for its mountainous landscape and traditional Sardinian culture.
  • A. Rascia
    Rascia is a historical region in the central Balkans that formed the medieval core of the Serbian state.
  • B. Urusemal
    Urusemal is a surname most notably associated with Joseph J. Urusemal, a politician from the Federated States of Micronesia who served as its president.
  • C. Yussois
    Yussois is the French demonym for inhabitants of the town of Yutz in northeastern France.
  • D. Oruzgan
    Oruzgan is a central Afghan province known for its mountainous terrain, tribal Pashtun population, and strategic role in recent conflicts.
  • E. Ussat
    Ussat is a small commune in the Ariège department of southwestern France, located in the Pyrenees and known for its proximity to notable caves and thermal springs.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328798a488190a5fad01c3c95584c completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c6ca1bc8190a6c4f675ec8e3a53 completed May 10, 2026, 8:06 a.m.
NEDg Description generation batch_6a003e3b113c819083e1abc512631e2b completed May 10, 2026, 8:13 a.m.
NED2 Entity disambiguation (via description) batch_6a003eb888e481908eb4ed77f86cf9f3 completed May 10, 2026, 8:15 a.m.
Created at: April 10, 2026, 5:09 a.m.