Triple
T24653467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Proportional Response |
E610318
|
entity |
| Predicate | hasFictionalPresident |
P155971
|
FINISHED |
| Object | Josiah Bartlet |
—
|
NE NERFINISHED |
How this triple was built (2 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: Josiah Bartlet | Statement: [A Proportional Response, hasFictionalPresident, Josiah Bartlet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPresident Context triple: [A Proportional Response, hasFictionalPresident, Josiah Bartlet]
-
A.
hasFictionalUSPresident
chosen
Indicates that a work of fiction features a character who serves as President of the United States within its narrative.
-
B.
hasFictionalLeader
Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
-
C.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
D.
hasFictionalSpokesperson
Indicates that an entity is represented or promoted by a spokesperson who is a fictional or imaginary character.
-
E.
hasPresidentProduced
Indicates that a president has created, authored, or otherwise produced the specified work or output.
- F. None of above.
Provenance (3 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_69e2c4d453248190a020354e93ef6282 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 2:34 a.m.