Triple
T12326936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Dennis Hastert |
E293853
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the given name of John Dennis Hastert, an American politician who served as the 51st Speaker of the United States House of Representatives.
|
E293853
|
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 Dennis Hastert, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Dennis Hastert, givenName, John]
-
A.
John
John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
-
B.
John
John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
-
C.
John
John is the given name of John Boyd-Carpenter, a prominent British Conservative politician who served in several senior government positions in the mid-20th century.
-
D.
John
John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
-
E.
John
John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
- 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 Dennis Hastert, givenName, John]
Generated description
John is the given name of John Dennis Hastert, an American politician who served as the 51st Speaker of the United States House of Representatives.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the given name of John Dennis Hastert, an American politician who served as the 51st Speaker of the United States House of Representatives.
-
A.
John
chosen
John is the first name of Dennis Hastert, the former Speaker of the United States House of Representatives.
-
B.
John
John is the given name of John Boehner, the American politician who served as the 53rd Speaker of the United States House of Representatives.
-
C.
John
John is the given name of John Sherman Cooper, a prominent American politician and long-serving U.S. Senator from Kentucky.
-
D.
John
John is the given name of John Edward Fogarty, an American politician who served as a U.S. Representative from Rhode Island.
-
E.
John
John is the given name of John Kitzhaber, an American politician and former governor of Oregon.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4f90a881908c5060dd197744d1 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63461cacc81909958fbd745e5d065 |
completed | May 2, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69f6356b545c819089a5f5b901afc5f2 |
completed | May 2, 2026, 5:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f636382ffc8190becfae41757a45d8 |
completed | May 2, 2026, 5:36 p.m. |
Created at: April 8, 2026, 9:53 p.m.