Triple
T109956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ichabod Crane |
E2224
|
entity |
| Predicate | storyFunction |
P7328
|
FINISHED |
| Object | vehicle for satire of superstition |
—
|
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: vehicle for satire of superstition | Statement: [Ichabod Crane, storyFunction, vehicle for satire of superstition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyFunction Context triple: [Ichabod Crane, storyFunction, vehicle for satire of superstition]
-
A.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
-
B.
numberOfStories
Indicates the total count of levels or floors that a structure or building has.
-
C.
narrativePerspective
Indicates the point of view or vantage from which a narrative is told, specifying the relationship between the storyteller and the events being described.
-
D.
scriptDirection
Indicates the direction in which a writing system or script is read or written (e.g., left-to-right, right-to-left, top-to-bottom).
-
E.
script
Indicates that an entity is associated with a written text or code (such as a screenplay, program, or written instructions) that defines its content or behavior.
- F. None of above. chosen
Provenance (4 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258b58efc8190959c86f73d67b744 |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25641058c8190b5b64509b35d8176 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a258b30f6c8190be2181f30c40e04d |
completed | Feb. 28, 2026, 2:53 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.