Triple

T29631048
Position Surface form Disambiguated ID Type / Status
Subject North Carolina State Ports Authority system E755571 entity
Predicate hasPart P35 FINISHED
Object Charlotte Inland Terminal
Charlotte Inland Terminal is an inland intermodal freight facility in Charlotte, North Carolina that connects regional shippers to the state’s seaports by rail and truck.
E1876213 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: Charlotte Inland Terminal | Statement: [North Carolina State Ports Authority system, hasPart, Charlotte Inland Terminal]
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: Charlotte Inland Terminal
Triple: [North Carolina State Ports Authority system, hasPart, Charlotte Inland Terminal]
Generated description
Charlotte Inland Terminal is an inland intermodal freight facility in Charlotte, North Carolina that connects regional shippers to the state’s seaports by rail and truck.

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_69f0ef88fbe081908f0ad90c1c413f1c completed April 28, 2026, 5:34 p.m.
NER Named-entity recognition batch_69f66e65c29481909283644a96b90eb8 completed May 2, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2661771e488190b23ef2b2a5ec3148 completed June 8, 2026, 6:30 a.m.
NEDg Description generation batch_6a26661afd388190a46079c263f911d2 completed June 8, 2026, 6:50 a.m.
NED2 Entity disambiguation (via description) batch_6a266a6166a08190a3ec83291c005e7b completed June 8, 2026, 7:08 a.m.
Created at: April 28, 2026, 6:41 p.m.