Triple

T5671320
Position Surface form Disambiguated ID Type / Status
Subject A91 Rome–Fiumicino motorway E124983 entity
Predicate managedBy P86 FINISHED
Object ANAS
ANAS is Italy’s national road agency responsible for the construction, maintenance, and management of much of the country’s road and motorway network.
 E535717 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: ANAS | Statement: [A91 Rome–Fiumicino motorway, managedBy, ANAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ANAS
Context triple: [A91 Rome–Fiumicino motorway, managedBy, ANAS]
  • A. ANAS
    ANAS is the primary state research institution in Azerbaijan, overseeing and coordinating scientific activities and academic research across the country.
  • B. Ansen
    Ansen is a small village in the Dutch province of Drenthe, located within the municipality of De Wolden.
  • C. ANE
    ANE is Apple's dedicated on-device neural processing unit designed to accelerate machine learning tasks efficiently on Apple hardware.
  • D. Anat
    Anat is a prominent Canaanite war and fertility goddess known for her fierce martial prowess and protective role in the ancient Levantine pantheon.
  • E. Asan
    Asan is a city in South Korea known for its hot springs, historical sites, and growing role as an industrial and educational center.
  • 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: ANAS
Triple: [A91 Rome–Fiumicino motorway, managedBy, ANAS]
Generated description
ANAS is Italy’s national road agency responsible for the construction, maintenance, and management of much of the country’s road and motorway network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ANAS
Target entity description: ANAS is Italy’s national road agency responsible for the construction, maintenance, and management of much of the country’s road and motorway network.
  • A. ANAS
    ANAS is the primary state research institution in Azerbaijan, overseeing and coordinating scientific activities and academic research across the country.
  • B. Ansen
    Ansen is a small village in the Dutch province of Drenthe, located within the municipality of De Wolden.
  • C. ANE
    ANE is Apple's dedicated on-device neural processing unit designed to accelerate machine learning tasks efficiently on Apple hardware.
  • D. Anat
    Anat is a prominent Canaanite war and fertility goddess known for her fierce martial prowess and protective role in the ancient Levantine pantheon.
  • E. Asan
    Asan is a city in South Korea known for its hot springs, historical sites, and growing role as an industrial and educational center.
  • 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_69c008295c808190acfe78915e7d656a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0236d3f94819095111c41a323612d completed March 22, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04db2c07c8190a3ee489146951d2d completed March 22, 2026, 8:14 p.m.
NEDg Description generation batch_69c04ee03d1c819096a5acf0358165c1 completed March 22, 2026, 8:19 p.m.
NED2 Entity disambiguation (via description) batch_69c04ffb0fb8819080dff2a9ec6eacb4 completed March 22, 2026, 8:24 p.m.
Created at: March 22, 2026, 3:43 p.m.