Triple
T14765724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maple Sylvie Bateman |
E346988
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Maple
Maple is a feminine given name that evokes the imagery of the maple tree and is sometimes chosen for its nature-inspired, modern sound.
|
E1119335
|
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: Maple | Statement: [Maple Sylvie Bateman, givenName, Maple]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maple Context triple: [Maple Sylvie Bateman, givenName, Maple]
-
A.
Maple
Maple is a comprehensive computer algebra system used for symbolic and numeric mathematics, modeling, and technical computing across education and research.
-
B.
Maples
Maples is the surname of Marla Maples, an American actress and television personality best known as the second wife of former U.S. President Donald Trump.
-
C.
Maple Jordan
Maple Jordan is the nickname of Canadian NBA player Andrew Wiggins, highlighting his high-flying, Jordan-like playing style and Canadian roots.
-
D.
Maple Library
Maple Library is a public community library serving residents of the Maple neighbourhood in Vaughan, Ontario.
-
E.
Maple GO Station
Maple GO Station is a commuter rail station in Maple, Ontario, serving as a local stop on GO Transit's regional rail network in the Greater Toronto Area.
- 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: Maple Triple: [Maple Sylvie Bateman, givenName, Maple]
Generated description
Maple is a feminine given name that evokes the imagery of the maple tree and is sometimes chosen for its nature-inspired, modern sound.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maple Target entity description: Maple is a feminine given name that evokes the imagery of the maple tree and is sometimes chosen for its nature-inspired, modern sound.
-
A.
Maple
Maple is a comprehensive computer algebra system used for symbolic and numeric mathematics, modeling, and technical computing across education and research.
-
B.
Maples
Maples is the surname of Marla Maples, an American actress and television personality best known as the second wife of former U.S. President Donald Trump.
-
C.
Maple Jordan
Maple Jordan is the nickname of Canadian NBA player Andrew Wiggins, highlighting his high-flying, Jordan-like playing style and Canadian roots.
-
D.
Maple Library
Maple Library is a public community library serving residents of the Maple neighbourhood in Vaughan, Ontario.
-
E.
Maple GO Station
Maple GO Station is a commuter rail station in Maple, Ontario, serving as a local stop on GO Transit's regional rail network in the Greater Toronto Area.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f576c881909da70627f5897c94 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cf4cef081909fa62125f43b36bc |
completed | May 8, 2026, 4:19 p.m. |
| NEDg | Description generation | batch_69fe1d66af94819091a84c2225cc7828 |
completed | May 8, 2026, 5:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe1e0089e08190a91f8683e683c371 |
completed | May 8, 2026, 5:31 p.m. |
Created at: April 10, 2026, 1:30 a.m.