Triple

T33586139
Position Surface form Disambiguated ID Type / Status
Subject Capital Airlines E860286 entity
Predicate predecessor P97 FINISHED
Object Pennsylvania Central Airlines
Pennsylvania Central Airlines was a mid-20th-century U.S. regional airline that later evolved into Capital Airlines, an important early carrier in American commercial aviation.
E2058649 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: Pennsylvania Central Airlines | Statement: [Capital Airlines, predecessor, Pennsylvania Central Airlines]
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: Pennsylvania Central Airlines
Triple: [Capital Airlines, predecessor, Pennsylvania Central Airlines]
Generated description
Pennsylvania Central Airlines was a mid-20th-century U.S. regional airline that later evolved into Capital Airlines, an important early carrier in American commercial aviation.

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_69f3497e70e48190951c94d072879bec completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f77444248190b8e6aac2d3b932e2 completed May 3, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a361191ced08190a6c8bf2f5b52d208 completed June 20, 2026, 4:05 a.m.
NEDg Description generation batch_6a361393388c8190a4fef33d2ea345ad completed June 20, 2026, 4:14 a.m.
NED2 Entity disambiguation (via description) batch_6a36140c54cc81909572920beb3ab881 completed June 20, 2026, 4:16 a.m.
Created at: May 1, 2026, 1:40 a.m.