Triple
T32171624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Hoynes |
E821722
|
entity |
| Predicate | positionInFictionalUniverse |
P87320
|
FINISHED |
| Object | Vice President under President Josiah Bartlet |
—
|
LITERAL FINISHED |
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: Vice President under President Josiah Bartlet | Statement: [John Hoynes, positionInFictionalUniverse, Vice President under President Josiah Bartlet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInFictionalUniverse Context triple: [John Hoynes, positionInFictionalUniverse, Vice President under President Josiah Bartlet]
-
A.
positionInFiction
chosen
Indicates that one entity holds a specific role, status, or placement within a fictional work or narrative.
-
B.
activeInFictionalUniverse
Indicates that an entity participates, operates, or has a role within a specified fictional universe or setting.
-
C.
isSetInFictionalUniverse
Indicates that a narrative work takes place within a specific fictional universe or setting.
-
D.
fictionalUniverseLocation
Indicates that one entity is a location or setting within the fictional universe to which the other entity belongs or in which it takes place.
-
E.
raisedInFictionalUniverse
Indicates that an entity was brought up or grew to maturity within a specified fictional universe or setting.
- 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_69f3490699a48190bbef96b198e8fade |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feabcda59481908f2bc13b46fcced1 |
completed | May 9, 2026, 3:36 a.m. |
| PD | Predicate disambiguation | batch_69feaabd63f88190b30dcf6dd2ea39d1 |
completed | May 9, 2026, 3:32 a.m. |
Created at: May 1, 2026, 12:33 a.m.