Triple
T27412604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington, North Carolina |
E692197
|
entity |
| Predicate | isFirstTownNamedAfter |
P162389
|
FINISHED |
| Object | George Washington in the United States |
—
|
LITERAL 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: George Washington in the United States | Statement: [Washington, North Carolina, isFirstTownNamedAfter, George Washington in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFirstTownNamedAfter Context triple: [Washington, North Carolina, isFirstTownNamedAfter, George Washington in the United States]
-
A.
isFirstTownOn
Indicates that a town is the first one encountered along a specified route, path, or sequence.
-
B.
hasCapitalNamedAfter
Indicates that one entity serves as the capital of another entity and that this capital is named after the other entity.
-
C.
isFirstCharteredTownOf
Indicates that one town holds the status of being the earliest or first officially chartered town relative to another specified context or region.
-
D.
wasFirstCapitalOf
Indicates that one place previously served as the earliest or original capital city of another political or administrative entity.
-
E.
hasTownNamedAfterHer
Indicates that a person has at least one town named in their honor.
- F. None of above. chosen
Provenance (4 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_69ef5205fc808190ad3efc5525b8e6d6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62cdb62608190a8e1c84a631de5ce |
completed | May 2, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f624c006788190a2f4d5015c96463f |
completed | May 2, 2026, 4:22 p.m. |
Created at: April 27, 2026, 12:32 p.m.