Triple
T29005789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth Davenport |
E736428
|
entity |
| Predicate | hasFictionalUniverseMedium |
P194001
|
FINISHED |
| Object | television |
—
|
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: television | Statement: [Beth Davenport, hasFictionalUniverseMedium, television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalUniverseMedium Context triple: [Beth Davenport, hasFictionalUniverseMedium, television]
-
A.
hasFictionalUniverseGenre
Indicates that a fictional universe is associated with a particular genre that characterizes its overall style, themes, or narrative type.
-
B.
hasFictionalUniverseProperty
Indicates that a fictional universe possesses a specific characteristic, attribute, or property.
-
C.
hasFictionalUniverseType
Indicates that an entity is associated with, or belongs to, a particular type or category of fictional universe.
-
D.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
E.
isSetInFictionalUniverse
Indicates that a narrative work takes place within a specific fictional universe or setting.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
| PDg | Predicate description generation | batch_69fd5d47da488190a4f2dbd44a0a83b2 |
completed | May 8, 2026, 3:49 a.m. |
Created at: April 28, 2026, 9:37 a.m.