Triple
T10411804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John, Abbot of Reading |
E245408
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John was an abbot of Reading Abbey, a senior monastic leader in the medieval English Benedictine community.
|
E863780
|
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: John | Statement: [John, Abbot of Reading, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John, Abbot of Reading, givenName, John]
-
A.
John
John is the given name of John Key, the former Prime Minister of New Zealand and leader of the National Party.
-
B.
John
John is the middle name of American entrepreneur Henry John Heinz, founder of the H. J. Heinz Company known for its ketchup and other food products.
-
C.
John
John is the given name of Australian cinematographer John Seale, known for his work on films such as "The English Patient" and "Mad Max: Fury Road."
-
D.
John
John is the given name of John Dustin Archbold, an American oil industry executive and key figure in the early history of Standard Oil.
-
E.
John
John is the given name of John Brisker, an American professional basketball player known for his time in the ABA and NBA and his mysterious disappearance in the 1970s.
- 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: John Triple: [John, Abbot of Reading, givenName, John]
Generated description
John was an abbot of Reading Abbey, a senior monastic leader in the medieval English Benedictine community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John was an abbot of Reading Abbey, a senior monastic leader in the medieval English Benedictine community.
-
A.
John
John is the given name of Saint John of Capistrano, a 15th-century Franciscan friar renowned as a preacher, theologian, and leader in the defense of Belgrade.
-
B.
John
John is the given name of John Stott, a prominent 20th-century English Anglican priest, theologian, and influential evangelical leader.
-
C.
John
John was a medieval English monarch who ruled as King John of England from 1199 to 1216 and is best known for sealing the Magna Carta.
-
D.
John
John is the given name of Sir John Woodville, a 15th-century English nobleman associated with the influential Woodville family during the Wars of the Roses.
-
E.
John
John is the given name of J. C. Squire, a prominent British poet, literary critic, and editor of the early 20th century.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9fc72d081908d81c71133973daf |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e9084fc81909e1d46a111a1ef2b |
completed | April 10, 2026, 4:37 a.m. |
| NEDg | Description generation | batch_69d886c325c4819089dac35eb26e7961 |
completed | April 10, 2026, 5:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d88dbbe97c8190861e08f3ff39f91b |
completed | April 10, 2026, 5:42 a.m. |
Created at: April 6, 2026, 12:10 p.m.