Triple
T11717866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis Pharcellus Church |
E278548
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Francis
Francis is a masculine given name of Latin origin, commonly associated with figures such as saints, popes, and writers.
|
E293255
|
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: Francis | Statement: [Francis Pharcellus Church, givenName, Francis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Francis Context triple: [Francis Pharcellus Church, givenName, Francis]
-
A.
Francis
Francis is the given first name of Daley Thompson, the celebrated British decathlete and double Olympic gold medalist.
-
B.
Francis
Francis is the given first name of the American actor Frank Morgan, best known for his role as the Wizard in "The Wizard of Oz."
-
C.
Francis
Francis is the middle name of Samuel Francis Du Pont, a prominent 19th-century U.S. Navy admiral from the Du Pont family.
-
D.
Francis
Francis is the given first name of Scottish former professional footballer Frank McAvennie.
-
E.
Francis
Francis was the given name of Francis of Lorraine, a 16th-century French nobleman who became Duke of Lorraine and played a significant role in European dynastic politics.
- 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: Francis Triple: [Francis Pharcellus Church, givenName, Francis]
Generated description
Francis is a masculine given name of Latin origin, commonly associated with figures such as saints, popes, and writers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Francis Target entity description: Francis is a masculine given name of Latin origin, commonly associated with figures such as saints, popes, and writers.
-
A.
Francis
chosen
Francis is a masculine given name of Latin origin, commonly used in English-speaking countries and associated with figures such as Saint Francis of Assisi and numerous historical and contemporary personalities.
-
B.
Francis
Francis is a common English surname of Latin origin, historically associated with people from France or those bearing the given name Francis.
-
C.
Francis
Francis is the papal name of the current head of the Roman Catholic Church, known for his emphasis on humility, social justice, and interfaith dialogue.
-
D.
Francis
Francis is the middle name of Patrick Francis Healy, a prominent 19th-century American Jesuit priest and president of Georgetown University.
-
E.
Francis
Francis is the given first name of Irish actor and singer Fra Fee, known for his work in film, television, and musical theatre.
- F. None of above.
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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4c10d988190842acd824135cf15 |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef83a9479c81909cbe63d81255a1bf |
completed | April 27, 2026, 3:41 p.m. |
| NEDg | Description generation | batch_69ef96b13be881908102ffa867f96c22 |
completed | April 27, 2026, 5:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69efb51113708190998b570c33b9d0e7 |
completed | April 27, 2026, 7:12 p.m. |
Created at: April 8, 2026, 9:40 p.m.