Triple
T14079421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LeMay |
E338825
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object |
Le May
Le May is a surname of French origin that can refer to various individuals, including writers, politicians, and other notable figures.
|
E1077019
|
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: Le May | Statement: [LeMay, hasVariantSpelling, Le May]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le May Context triple: [LeMay, hasVariantSpelling, Le May]
-
A.
L'Alizé
L'Alizé is a 2000 French pop song by singer Alizée that became a major hit across Europe and helped launch her international career.
-
B.
Le Marin
Le Marin is a coastal town in southern Martinique known for its large marina and role as a major yachting and boating hub in the Caribbean.
-
C.
Lisberg
Lisberg is a Danish-origin surname most notably associated with figures such as Jens Oliver Lisberg.
-
D.
L’Espoir
L’Espoir is a 1937 novel by André Malraux that portrays the political and human drama of the Spanish Civil War.
-
E.
Navigo Découverte
Navigo Découverte is an anonymous, reloadable contactless travel card used by residents and visitors to access public transportation across the Île-de-France (Paris) region.
- 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: Le May Triple: [LeMay, hasVariantSpelling, Le May]
Generated description
Le May is a surname of French origin that can refer to various individuals, including writers, politicians, and other notable figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Le May Target entity description: Le May is a surname of French origin that can refer to various individuals, including writers, politicians, and other notable figures.
-
A.
L'Alizé
L'Alizé is a 2000 French pop song by singer Alizée that became a major hit across Europe and helped launch her international career.
-
B.
Le Marin
Le Marin is a coastal town in southern Martinique known for its large marina and role as a major yachting and boating hub in the Caribbean.
-
C.
Lisberg
Lisberg is a Danish-origin surname most notably associated with figures such as Jens Oliver Lisberg.
-
D.
L’Espoir
L’Espoir is a 1937 novel by André Malraux that portrays the political and human drama of the Spanish Civil War.
-
E.
Navigo Découverte
Navigo Découverte is an anonymous, reloadable contactless travel card used by residents and visitors to access public transportation across the Île-de-France (Paris) region.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5e027881908f610f5bab7598d4 |
completed | April 14, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb672c08081908e1ff9030745776a |
completed | May 7, 2026, 3:57 p.m. |
| NEDg | Description generation | batch_69fcc1208a1481908b9f9a49b9c5ca5b |
completed | May 7, 2026, 4:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcc19f735c8190a4e765f34abaa672 |
completed | May 7, 2026, 4:45 p.m. |
Created at: April 9, 2026, 10:21 p.m.