Triple
T6612844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Berwick |
E149277
|
entity |
| Predicate | titleStatusInFrance |
P27128
|
FINISHED |
| Object | recognized in the French peerage |
—
|
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: recognized in the French peerage | Statement: [Duke of Berwick, titleStatusInFrance, recognized in the French peerage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleStatusInFrance Context triple: [Duke of Berwick, titleStatusInFrance, recognized in the French peerage]
-
A.
statusInFrance
chosen
Indicates the legal, social, or official standing or condition that an entity has within the jurisdiction of France.
-
B.
titleStatus
Indicates the current legal or administrative state of a title (such as ownership, validity, or processing stage) in relation to an entity or record.
-
C.
statusInRepublicOfIreland
Indicates the legal or official status that an entity holds within the jurisdiction of the Republic of Ireland.
-
D.
countrySpecificStatus
Indicates a status or condition that is defined or applied specifically in the context of a particular country.
-
E.
statusInUnitedStates
Indicates the legal or official standing that an entity holds within the jurisdiction of the United States.
- 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_69c687ebc680819094caf71faba2efe2 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cf3796d08190a26e988386089447 |
completed | March 27, 2026, 6:40 p.m. |
| PD | Predicate disambiguation | batch_69c6acfed25481909cac74c84a9fe088 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:57 p.m.