Triple
T295415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katrina Van Tassel |
E6081
|
entity |
| Predicate | associatedWithTheme |
P2830
|
FINISHED |
| Object | romantic rivalry |
—
|
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: romantic rivalry | Statement: [Katrina Van Tassel, associatedWithTheme, romantic rivalry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithTheme Context triple: [Katrina Van Tassel, associatedWithTheme, romantic rivalry]
-
A.
associatedWithText
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
-
B.
containsThemeArea
Indicates that one entity includes or encompasses a specific thematic area as part of its scope or content.
-
C.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
D.
hasCentralTheme
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
-
E.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e9e273f88190ac5355d1310376ed |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e9368894819093eeae4347dfcc5a |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.