Triple

T15650156
Position Surface form Disambiguated ID Type / Status
Subject Comiso Airport E376288 entity
Predicate nearbyCity P350 FINISHED
Object Syracuse E148060 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: Syracuse | Statement: [Comiso Airport, nearbyCity, Syracuse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Syracuse
Context triple: [Comiso Airport, nearbyCity, Syracuse]
  • A. Syracuse
    Syracuse is a mid-sized city in central New York State known for Syracuse University, its role as a regional economic and cultural hub, and its snowy winters.
  • B. Syracuse chosen
    Syracuse is an ancient and historically significant city on the eastern coast of Sicily, renowned as a powerful Greek colony and cultural center in antiquity.
  • C. Syracuse
    Syracuse is a suburban city in Davis County, northern Utah, known for its rapid growth and proximity to the Great Salt Lake and Antelope Island.
  • D. Utica
    Utica was an ancient Phoenician colony in North Africa that became one of the earliest and most important urban centers in the western Mediterranean.
  • E. Utica
    Utica is a small town in Hinds County, Mississippi, known for its rural character and historic Southern setting.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04eeed2d48190a7a8a618d90012d0 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff755e0f2c819088293d8a55d7883a completed May 9, 2026, 5:56 p.m.
Created at: April 10, 2026, 4:15 a.m.