Triple
T13046152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermín Lafitte |
E327327
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lafitte
Lafitte is a French-origin surname borne by various notable individuals, including figures in politics, the arts, and sports.
|
E1018232
|
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: Lafitte | Statement: [Fermín Lafitte, familyName, Lafitte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lafitte Context triple: [Fermín Lafitte, familyName, Lafitte]
-
A.
San Nicolas
San Nicolas is a town in Aruba known for its significant Afro-Aruban community and cultural influence.
-
B.
San Nicolas
San Nicolas is a historic riverside district of Manila, Philippines, known for its old commercial houses, narrow streets, and proximity to the walled city of Intramuros.
-
C.
San Nicolas
San Nicolas is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
-
D.
Chenier
Chenier is a French-origin surname borne by various notable individuals, including athletes, musicians, and public figures.
-
E.
Beau Vallon
Beau Vallon is a popular coastal district and beach resort area on the island of Mahé in Seychelles, known for its wide sandy bay, clear waters, and tourism infrastructure.
- 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: Lafitte Triple: [Fermín Lafitte, familyName, Lafitte]
Generated description
Lafitte is a French-origin surname borne by various notable individuals, including figures in politics, the arts, and sports.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lafitte Target entity description: Lafitte is a French-origin surname borne by various notable individuals, including figures in politics, the arts, and sports.
-
A.
San Nicolas
San Nicolas is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
-
B.
San Nicolas
San Nicolas is a historic riverside district of Manila, Philippines, known for its old commercial houses, narrow streets, and proximity to the walled city of Intramuros.
-
C.
San Nicolas
San Nicolas is a town in Aruba known for its significant Afro-Aruban community and cultural influence.
-
D.
Chenier
Chenier is a French-origin surname borne by various notable individuals, including athletes, musicians, and public figures.
-
E.
Beau Vallon
Beau Vallon is a popular coastal district and beach resort area on the island of Mahé in Seychelles, known for its wide sandy bay, clear waters, and tourism infrastructure.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9805125e481908ed56f708de98a9e |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd8f1308190992c0bd832e1b05e |
completed | May 3, 2026, 4:15 a.m. |
| NEDg | Description generation | batch_69f6cd98d29c8190b33cb2cc6c477b1d |
completed | May 3, 2026, 4:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ce23ca208190960409130c4c52a9 |
completed | May 3, 2026, 4:25 a.m. |
Created at: April 9, 2026, 8:56 p.m.