Triple
T14860766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Tour to the East in the Years 1763 and 1764 |
E349480
|
entity |
| Predicate | featuresProtagonistNationality |
P14334
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [A Tour to the East in the Years 1763 and 1764, featuresProtagonistNationality, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresProtagonistNationality Context triple: [A Tour to the East in the Years 1763 and 1764, featuresProtagonistNationality, English]
-
A.
protagonistNationality
chosen
Indicates the country or national identity to which the protagonist of a work is associated or belongs.
-
B.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
C.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
D.
protagonistBasedOn
Indicates that a fictional work’s main character is modeled on, inspired by, or derived from a particular real or fictional person or entity.
-
E.
protagonistEthnicity
Indicates the ethnic background or cultural heritage associated with a work’s main character.
- F. None of above.
Provenance (3 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded573cba881908d6d9ac570a64e5f |
completed | April 15, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:54 a.m.