Triple

T3368381
Position Surface form Disambiguated ID Type / Status
Subject Picenum E70891 entity
Predicate hasCapital P204 FINISHED
Object Asculum
Asculum was an important ancient city in central Italy, historically serving as the chief urban center of the Piceni people.
 E352707 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: Asculum | Statement: [Picenum, hasCapital, Asculum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Asculum
Context triple: [Picenum, hasCapital, Asculum]
  • A. Arpinum
    Arpinum is an ancient Italian town in Latium best known as the birthplace of the Roman statesman and orator Cicero.
  • B. Clusium
    Clusium was an important ancient Etruscan city, known for its strategic location in central Italy and its significant role in early Roman history.
  • C. Selasca
    Selasca is a small locality in northern Italy notable as the place where the mathematician Bernhard Riemann died.
  • D. Maenza
    Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
  • E. Marrucini
    The Marrucini were an ancient Italic tribe of central Italy, closely associated with neighboring peoples like the Marsi and Paeligni and later incorporated into the Roman state.
  • 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: Asculum
Triple: [Picenum, hasCapital, Asculum]
Generated description
Asculum was an important ancient city in central Italy, historically serving as the chief urban center of the Piceni people.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Asculum
Target entity description: Asculum was an important ancient city in central Italy, historically serving as the chief urban center of the Piceni people.
  • A. Arpinum
    Arpinum is an ancient Italian town in Latium best known as the birthplace of the Roman statesman and orator Cicero.
  • B. Clusium
    Clusium was an important ancient Etruscan city, known for its strategic location in central Italy and its significant role in early Roman history.
  • C. Selasca
    Selasca is a small locality in northern Italy notable as the place where the mathematician Bernhard Riemann died.
  • D. Maenza
    Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
  • E. Marrucini
    The Marrucini were an ancient Italic tribe of central Italy, closely associated with neighboring peoples like the Marsi and Paeligni and later incorporated into the Roman state.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb28a813c81909d1c71fe577e6681 completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3343664cc81909793820377b4bdc1 completed March 12, 2026, 9:46 p.m.
NEDg Description generation batch_69b334f75e708190aed8b388c9ea55d2 completed March 12, 2026, 9:49 p.m.
NED2 Entity disambiguation (via description) batch_69b3359ab56881908e247ba54c7dd6c7 completed March 12, 2026, 9:52 p.m.
Created at: March 8, 2026, 3:13 p.m.