Triple

T24321435
Position Surface form Disambiguated ID Type / Status
Subject Peter O. Knight Airport E612972 entity
Predicate isPartOf P10 FINISHED
Object Tampa Bay area airport system
The Tampa Bay area airport system is a regional network of airports serving the greater Tampa Bay region in Florida, encompassing major commercial hubs as well as smaller general aviation facilities.
E1627018 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: Tampa Bay area airport system | Statement: [Peter O. Knight Airport, isPartOf, Tampa Bay area airport system]
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: Tampa Bay area airport system
Triple: [Peter O. Knight Airport, isPartOf, Tampa Bay area airport system]
Generated description
The Tampa Bay area airport system is a regional network of airports serving the greater Tampa Bay region in Florida, encompassing major commercial hubs as well as smaller general aviation facilities.

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_69e2d7da491c8190b6e6218af50923db completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292ac7fc08190993f707f2f97e7f5 completed April 29, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc9e4a1748190b5637b682458124a completed May 22, 2026, 3:13 a.m.
NEDg Description generation batch_6a0fcade9db88190b79f8f03c9b5f51f completed May 22, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcb724a888190838a30e05e556421 completed May 22, 2026, 3:20 a.m.
Created at: April 18, 2026, 1:51 a.m.