Triple
T40114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the Garter |
E792
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object |
St George
St George is a Christian martyr and legendary dragon-slaying warrior venerated as a patron saint of England and chivalry.
|
E3419
|
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: St George | Statement: [Order of the Garter, associatedWith, St George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St George Context triple: [Order of the Garter, associatedWith, St George]
-
A.
Nelson
Nelson is a common English-language surname borne by numerous notable figures across politics, sports, entertainment, and academia.
-
B.
London Breed
London Breed is an American politician serving as the mayor of San Francisco and the first Black woman to hold that office.
-
C.
Gloucester
Gloucester is a historic coastal city in northeastern Massachusetts known for its long-standing fishing industry and maritime heritage.
-
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.
Lionel Hall
Lionel Hall is an undergraduate dormitory building located within Harvard University's historic Harvard Yard.
- 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: St George Triple: [Order of the Garter, associatedWith, St George]
Generated description
St George is a Christian martyr and legendary dragon-slaying warrior venerated as a patron saint of England and chivalry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: St George Target entity description: St George is a Christian martyr and legendary dragon-slaying warrior venerated as a patron saint of England and chivalry.
-
A.
Gallic rooster
The Gallic rooster is a traditional emblem of France, symbolizing the nation’s pride, vigilance, and cultural identity.
-
B.
Nelson
Nelson is a common English-language surname borne by numerous notable figures across politics, sports, entertainment, and academia.
-
C.
London Breed
London Breed is an American politician serving as the mayor of San Francisco and the first Black woman to hold that office.
-
D.
Gloucester
Gloucester is a historic coastal city in northeastern Massachusetts known for its long-standing fishing industry and maritime heritage.
-
E.
Herbert
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24adf3640819095576e072fb5d9a8 |
completed | Feb. 28, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a24e6222408190bc317b90aea16849 |
completed | Feb. 28, 2026, 2:09 a.m. |
| NEDg | Description generation | batch_69a250f6c0308190affd58f1bfa0c261 |
completed | Feb. 28, 2026, 2:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a251b471688190b067c5db8f03ac47 |
completed | Feb. 28, 2026, 2:23 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.