Triple
T27186527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Keeler |
E683347
|
entity |
| Predicate | positionInFictionalContinuity |
P87320
|
FINISHED |
| Object | successor to President David Palmer |
—
|
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: successor to President David Palmer | Statement: [John Keeler, positionInFictionalContinuity, successor to President David Palmer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInFictionalContinuity Context triple: [John Keeler, positionInFictionalContinuity, successor to President David Palmer]
-
A.
positionInFiction
chosen
Indicates that one entity holds a specific role, status, or placement within a fictional work or narrative.
-
B.
locatedInFictionalContext
Indicates that one entity exists or occurs within the setting or universe of a fictional work associated with another entity.
-
C.
locationWithinFiction
Indicates that one fictional location is situated inside or contained within another fictional location.
-
D.
activeInFictionalUniverse
Indicates that an entity participates, operates, or has a role within a specified fictional universe or setting.
-
E.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
- 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_69eefad140408190b8586fdebcf9af46 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 27, 2026, 9:30 a.m.