Triple
T21860254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Igor (later Frankenstein films) |
E539740
|
entity |
| Predicate | hasStereotypeElement |
P91566
|
FINISHED |
| Object | Eastern European accent |
—
|
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: Eastern European accent | Statement: [Igor (later Frankenstein films), hasStereotypeElement, Eastern European accent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStereotypeElement Context triple: [Igor (later Frankenstein films), hasStereotypeElement, Eastern European accent]
-
A.
hasStereotypeAssociation
chosen
Indicates that one entity is associated with another through a stereotype, implying a generalized or oversimplified characterization rather than an individually grounded attribute.
-
B.
hasElementType
Indicates that something is composed of or contains elements that are of a specified type.
-
C.
containsTrait
Indicates that one entity possesses, exhibits, or is characterized by a specified trait.
-
D.
hasContainmentType
Indicates the specific way in which one entity is contained within or enclosed by another.
-
E.
hasContainment
Indicates that one entity spatially or logically encloses, includes, or holds another within its bounds.
- 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_69e0c47829648190bbe2d1d7033768ec |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0d63a22b88190b59b13e7b4788195 |
completed | April 28, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:56 p.m.