Triple
T28665970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Hanscom (It Chapter Two) |
E725586
|
entity |
| Predicate | flashbackDepictionBy |
P139821
|
FINISHED |
| Object | Jeremy Ray Taylor |
—
|
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: Jeremy Ray Taylor | Statement: [Ben Hanscom (It Chapter Two), flashbackDepictionBy, Jeremy Ray Taylor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flashbackDepictionBy Context triple: [Ben Hanscom (It Chapter Two), flashbackDepictionBy, Jeremy Ray Taylor]
-
A.
portrayedInFlashbacks
chosen
Indicates that an entity appears or is depicted specifically within flashback scenes of a narrative work.
-
B.
laterDepiction
Indicates that one depiction represents a subsequent or later version, portrayal, or representation of the same subject as another depiction.
-
C.
companionActorInFlashback
Indicates that one actor appears as a companion to another actor specifically within a flashback sequence.
-
D.
depictionAction
Indicates an action in which one entity visually represents, illustrates, or portrays another entity.
-
E.
depictionDetail
Indicates that one depiction provides additional detail, refinement, or a closer view of what is shown in another depiction.
- 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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 5:01 a.m.