Triple
T25993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne, Queen of Great Britain |
E519
|
entity |
| Predicate | style |
P87
|
FINISHED |
| Object |
Her Majesty
Her Majesty is the formal royal style used to address or refer to a reigning queen such as Anne, Queen of Great Britain.
|
E3496
|
NE FINISHED |
How this triple was built (4 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: Her Majesty | Statement: [Anne, Queen of Great Britain, style, Her Majesty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Her Majesty Context triple: [Anne, Queen of Great Britain, style, Her Majesty]
-
A.
Crown
The Crown is the institution representing the British monarchy and the executive authority of the state, distinct from Parliament and the judiciary.
-
B.
Emperor
The Emperor is the ceremonial monarch and symbolic head of state of Japan, representing the continuity and unity of the Japanese nation.
-
C.
Mr. Secretary
Mr. Secretary is the formal style of address traditionally used for the United States Secretary of Defense.
-
D.
Herbert
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
-
E.
Shirley
Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Her Majesty Triple: [Anne, Queen of Great Britain, style, Her Majesty]
Generated description
Her Majesty is the formal royal style used to address or refer to a reigning queen such as Anne, Queen of Great Britain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Her Majesty Target entity description: Her Majesty is the formal royal style used to address or refer to a reigning queen such as Anne, Queen of Great Britain.
-
A.
Crown
The Crown is the institution representing the British monarchy and the executive authority of the state, distinct from Parliament and the judiciary.
-
B.
Emperor
The Emperor is the ceremonial monarch and symbolic head of state of Japan, representing the continuity and unity of the Japanese nation.
-
C.
Mr. Secretary
Mr. Secretary is the formal style of address traditionally used for the United States Secretary of Defense.
-
D.
Herbert
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
-
E.
Shirley
Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
- F. None of above. chosen
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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246776cf48190aca9855cb07e8d89 |
completed | Feb. 28, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a24e5b531481909078feeee5cf26e2 |
completed | Feb. 28, 2026, 2:09 a.m. |
| NEDg | Description generation | batch_69a2506ad2ac8190b5a61c3fb3890d47 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a25147eccc8190b6151a03b064d31c |
completed | Feb. 28, 2026, 2:22 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.