Triple

T1906871
Position Surface form Disambiguated ID Type / Status
Subject Via Aemilia E38023 entity
Predicate connects P390 FINISHED
Object Mutina
Mutina was an important ancient Roman city in northern Italy, known today as Modena.
 E212294 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: Mutina | Statement: [Via Aemilia, connects, Mutina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mutina
Context triple: [Via Aemilia, connects, Mutina]
  • A. Canova
    Canova was a renowned Italian Neoclassical sculptor celebrated for his marble masterpieces depicting mythological and historical subjects.
  • B. Clementia
    Clementia is a feminine given name of Latin origin associated with the virtue of mercy and clemency.
  • C. Selasca
    Selasca is a small locality in northern Italy notable as the place where the mathematician Bernhard Riemann died.
  • D. Antium
    Antium was an ancient coastal town in Latium, Italy, notable as a resort and birthplace of several Roman emperors, including Caligula and Nero.
  • E. Clusium
    Clusium was an important ancient Etruscan city, known for its strategic location in central Italy and its significant role in early Roman history.
  • 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: Mutina
Triple: [Via Aemilia, connects, Mutina]
Generated description
Mutina was an important ancient Roman city in northern Italy, known today as Modena.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mutina
Target entity description: Mutina was an important ancient Roman city in northern Italy, known today as Modena.
  • A. Canova
    Canova was a renowned Italian Neoclassical sculptor celebrated for his marble masterpieces depicting mythological and historical subjects.
  • B. Clementia
    Clementia is a feminine given name of Latin origin associated with the virtue of mercy and clemency.
  • C. Selasca
    Selasca is a small locality in northern Italy notable as the place where the mathematician Bernhard Riemann died.
  • D. Antium
    Antium was an ancient coastal town in Latium, Italy, notable as a resort and birthplace of several Roman emperors, including Caligula and Nero.
  • E. Clusium
    Clusium was an important ancient Etruscan city, known for its strategic location in central Italy and its significant role in early Roman history.
  • 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_69a8862a26088190aae5243695aeefc0 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1b3217081909004ad7f687b4216 completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeafb063481908a08f5570acc5b57 completed March 8, 2026, 9:32 p.m.
NEDg Description generation batch_69adec22c5e48190af85fa4a1d4c5d8d completed March 8, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_69adec9a840c8190a03f4de0f03a0e10 completed March 8, 2026, 9:39 p.m.
Created at: March 4, 2026, 7:35 p.m.