Triple
T8450053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Turner’s Come and Gone |
E199776
|
entity |
| Predicate | timeInNarrativeFollows |
P43308
|
FINISHED |
| Object | events of slavery and Reconstruction |
—
|
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: events of slavery and Reconstruction | Statement: [Joe Turner’s Come and Gone, timeInNarrativeFollows, events of slavery and Reconstruction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeInNarrativeFollows Context triple: [Joe Turner’s Come and Gone, timeInNarrativeFollows, events of slavery and Reconstruction]
-
A.
followsTime
chosen
Indicates that one event, state, or time period occurs after and in temporal succession to another.
-
B.
timeOfNarrative
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
C.
followsBetween
Indicates that one entity comes after or succeeds another entity within a specified context or sequence.
-
D.
followsStoryOf
Indicates that one narrative, account, or storyline continues from, is based on, or is derived from the events or structure of another.
-
E.
narrativePresence
Indicates that an entity appears or is involved within the narrative or storyline of another entity.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44707b88190b3d8b30c45ef4496 |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.