Triple
T4051798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VMAP |
E84601
|
entity |
| Predicate | relationshipToVAST |
P37
|
FINISHED |
| Object | wraps or references VAST ad responses for each ad break |
—
|
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: wraps or references VAST ad responses for each ad break | Statement: [VMAP, relationshipToVAST, wraps or references VAST ad responses for each ad break]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToVAST Context triple: [VMAP, relationshipToVAST, wraps or references VAST ad responses for each ad break]
-
A.
valueRelation
Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
-
B.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
C.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
D.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb8539148190990468c1429be9dd |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.