Triple
T6339419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura |
E142585
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Laure
Laure is a feminine given name, primarily used in French-speaking countries, that is a variant of the name Laura.
|
E587352
|
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: Laure | Statement: [Laura, hasVariant, Laure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laure Context triple: [Laura, hasVariant, Laure]
-
A.
Laureline
Laureline is a courageous and quick-witted space-time agent who partners with Valerian in the sci-fi universe of "Valerian and the City of a Thousand Planets."
-
B.
Valleiry
Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
-
C.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
-
D.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
-
E.
Laur
Laur is a rural municipality in the province of Nueva Ecija in the Philippines, known for its agricultural landscape and proximity to the Sierra Madre mountain range.
- 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: Laure Triple: [Laura, hasVariant, Laure]
Generated description
Laure is a feminine given name, primarily used in French-speaking countries, that is a variant of the name Laura.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laure Target entity description: Laure is a feminine given name, primarily used in French-speaking countries, that is a variant of the name Laura.
-
A.
Laureline
Laureline is a courageous and quick-witted space-time agent who partners with Valerian in the sci-fi universe of "Valerian and the City of a Thousand Planets."
-
B.
Valleiry
Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
-
C.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
-
D.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
-
E.
Laur
Laur is a rural municipality in the province of Nueva Ecija in the Philippines, known for its agricultural landscape and proximity to the Sierra Madre mountain range.
- 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0654fb774819087bffb8b966a790a |
completed | March 22, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c604352f148190b5accc28462256ad |
completed | March 27, 2026, 4:14 a.m. |
| NEDg | Description generation | batch_69c620db73dc8190b9e75e0a9d01ff5a |
completed | March 27, 2026, 6:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c624e2b3c081908e5c05da38121631 |
completed | March 27, 2026, 6:34 a.m. |
Created at: March 22, 2026, 4:30 p.m.