Triple
T24215267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lana Turner as Cynthia Potter |
E600678
|
entity |
| Predicate | addsElement |
P3097
|
FINISHED |
| Object | romantic allure |
—
|
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 allure | Statement: [Lana Turner as Cynthia Potter, addsElement, romantic allure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addsElement Context triple: [Lana Turner as Cynthia Potter, addsElement, romantic allure]
-
A.
addsClass
Indicates that one entity introduces or appends a class (such as a classification, type, or code) to another entity.
-
B.
setElement
Indicates that a particular element is included as a member of a specified set.
-
C.
definesElement
Indicates that one entity specifies or determines the nature, structure, or identity of another entity as its defining element.
-
D.
usesElement
chosen
Indicates that one entity makes use of, incorporates, or depends on a specified element in its structure, function, or behavior.
-
E.
addedFor
Indicates that one entity was created, included, or introduced specifically for the benefit, use, or purpose 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_69e2953344c48190875730c7d52112a0 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f282077c688190ae50c3929b22328c |
completed | April 29, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:58 p.m.