Triple
T1621724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grant Wood |
E35045
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Grant
Grant is a masculine given name of English origin that is commonly used in the United States and other English-speaking countries.
|
E182443
|
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: Grant | Statement: [Grant Wood, givenName, Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grant Context triple: [Grant Wood, givenName, Grant]
-
A.
Jones
Jones is a common English-language surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and science.
-
B.
Red Grant
Red Grant is a ruthless, psychopathic assassin and primary antagonist in the James Bond franchise, most prominently appearing as SPECTRE’s top killer in the film and novel "From Russia, with Love."
-
C.
Graham
Graham is the surname of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics empire.
-
D.
Graham
Graham is a masculine given name of English origin, historically derived from a surname and commonly used in English-speaking countries.
-
E.
Williams
Williams is a common English surname borne by numerous notable figures across sports, politics, arts, and entertainment.
- 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: Grant Triple: [Grant Wood, givenName, Grant]
Generated description
Grant is a masculine given name of English origin that is commonly used in the United States and other English-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grant Target entity description: Grant is a masculine given name of English origin that is commonly used in the United States and other English-speaking countries.
-
A.
Jones
Jones is a common English-language surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and science.
-
B.
Red Grant
Red Grant is a ruthless, psychopathic assassin and primary antagonist in the James Bond franchise, most prominently appearing as SPECTRE’s top killer in the film and novel "From Russia, with Love."
-
C.
Graham
Graham is the surname of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics empire.
-
D.
Graham
Graham is a masculine given name of English origin, historically derived from a surname and commonly used in English-speaking countries.
-
E.
Williams
Williams is a common English surname borne by numerous notable figures across sports, politics, arts, and entertainment.
- 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909b1fc788190b38c0aa4ccc2e953 |
completed | March 5, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad51d2cbb481908bc74cecdc023547 |
completed | March 8, 2026, 10:39 a.m. |
| NEDg | Description generation | batch_69ad5277c64481909ffe991fd4579d0d |
completed | March 8, 2026, 10:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad52f8dda48190969a31b85b1d5134 |
completed | March 8, 2026, 10:44 a.m. |
Created at: March 4, 2026, 7:28 p.m.