Triple

T11745242
Position Surface form Disambiguated ID Type / Status
Subject Tagliamento River E279261 entity
Predicate passesNear P416 FINISHED
Object Latisana
Latisana is a town in northeastern Italy’s Friuli Venezia Giulia region, known historically as a river port and agricultural center near the Adriatic coast.
 E944575 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: Latisana | Statement: [Tagliamento River, passesNear, Latisana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Latisana
Context triple: [Tagliamento River, passesNear, Latisana]
  • A. Laka
    Laka is a dialect of the Sara language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • B. Lusiana
    Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
  • C. Tola
    Tola is a minor judge of Israel mentioned in the biblical Book of Judges, known for leading and delivering Israel for 23 years after the time of Abimelech.
  • D. Sanana
    Sanana is the principal island and administrative center of the Sula Islands group in North Maluku, Indonesia.
  • E. Lunyole
    Lunyole is a Bantu language spoken in eastern Uganda, particularly associated with the Banyole people.
  • 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: Latisana
Triple: [Tagliamento River, passesNear, Latisana]
Generated description
Latisana is a town in northeastern Italy’s Friuli Venezia Giulia region, known historically as a river port and agricultural center near the Adriatic coast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Latisana
Target entity description: Latisana is a town in northeastern Italy’s Friuli Venezia Giulia region, known historically as a river port and agricultural center near the Adriatic coast.
  • A. Laka
    Laka is a dialect of the Sara language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • B. Lusiana
    Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
  • C. Tola
    Tola is a minor judge of Israel mentioned in the biblical Book of Judges, known for leading and delivering Israel for 23 years after the time of Abimelech.
  • D. Sanana
    Sanana is the principal island and administrative center of the Sula Islands group in North Maluku, Indonesia.
  • E. Lunyole
    Lunyole is a Bantu language spoken in eastern Uganda, particularly associated with the Banyole people.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4f2a38c8190a682d8dae1ab9415 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019e4f0988190afe0b92f4c9d8073 completed April 28, 2026, 2:22 a.m.
NEDg Description generation batch_69f043b3c51c8190a764433e86f1333e completed April 28, 2026, 5:20 a.m.
NED2 Entity disambiguation (via description) batch_69f05aa351888190a31092e6a9aee26b completed April 28, 2026, 6:58 a.m.
Created at: April 8, 2026, 9:41 p.m.