Triple

T11129477
Position Surface form Disambiguated ID Type / Status
Subject Nestor of Tarsus E263238 entity
Predicate associatedWith P37 FINISHED
Object Tarsus E47685 NE FINISHED

How this triple was built (2 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: Tarsus | Statement: [Nestor of Tarsus, associatedWith, Tarsus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarsus
Context triple: [Nestor of Tarsus, associatedWith, Tarsus]
  • A. Tarsus chosen
    Tarsus is an ancient city in Cilicia (in modern-day Turkey) known as a major cultural and commercial center of the Roman Empire and as the birthplace of the Apostle Paul.
  • B. Smyrna
    Smyrna was a major Aegean port city (modern-day İzmir in Turkey) that served as a key commercial and cultural hub in the Ottoman Empire.
  • C. Smyrna
    Smyrna is a suburban city in the Atlanta metropolitan area known for its residential communities, parks, and proximity to major Atlanta attractions.
  • D. Smyrna
    Smyrna is a small historic town in central Delaware known for its colonial-era roots and location along major transportation routes.
  • E. Edessa
    Edessa is a historic city in northern Greece renowned for its picturesque waterfalls and ancient heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e830e804819097fcc3826d84dab8 completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6037fdf80819091fb2c8bf128582d completed April 20, 2026, 10:44 a.m.
Created at: April 8, 2026, 9:28 p.m.