Triple
T18168244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Gower |
E434950
|
entity |
| Predicate | laterLifeStatusInOriginalTimeline |
P99598
|
FINISHED |
| Object | respected member of Bedford Falls |
—
|
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: respected member of Bedford Falls | Statement: [Mr. Gower, laterLifeStatusInOriginalTimeline, respected member of Bedford Falls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterLifeStatusInOriginalTimeline Context triple: [Mr. Gower, laterLifeStatusInOriginalTimeline, respected member of Bedford Falls]
-
A.
characterStatusInOriginalTimeline
chosen
Indicates the state or condition a character has within the original, unaltered timeline of events.
-
B.
deathInOriginalTimeline
Indicates that an entity dies within the events of the original, unaltered timeline.
-
C.
alternateTimelineName
Indicates that one entity is the name or designation used for another entity in an alternate or parallel timeline.
-
D.
hasAlternateTimeline
Indicates that an entity exists or occurs in a different possible or parallel timeline relative to another reference timeline.
-
E.
laterStatus
Indicates that one entity represents a subsequent or resulting status or condition of another entity in time.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df52f8b08190ab2c4d76b510cd28 |
completed | April 19, 2026, 1:57 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.