Triple

T30017093
Position Surface form Disambiguated ID Type / Status
Subject Phoebus, Virginia E762623 entity
Predicate countyEquivalent P3911 FINISHED
Object Independent city of Hampton
The Independent city of Hampton is a coastal city in southeastern Virginia known for its deep colonial roots, military installations, and proximity to the Chesapeake Bay.
E1894232 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: Independent city of Hampton | Statement: [Phoebus, Virginia, countyEquivalent, Independent city of Hampton]
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: Independent city of Hampton
Triple: [Phoebus, Virginia, countyEquivalent, Independent city of Hampton]
Generated description
The Independent city of Hampton is a coastal city in southeastern Virginia known for its deep colonial roots, military installations, and proximity to the Chesapeake Bay.

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_69f2246b0c84819094f1250b6a02d277 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6798536288190bd0541e060dd9f6a completed May 2, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27221520108190ba5a553bbf336075 completed June 8, 2026, 8:12 p.m.
NEDg Description generation batch_6a272388d9c48190a4ed6758fa181b41 completed June 8, 2026, 8:18 p.m.
NED2 Entity disambiguation (via description) batch_6a27245326ac8190a1d398727fb54bc8 completed June 8, 2026, 8:21 p.m.
Created at: April 29, 2026, 6:46 p.m.