Triple
T18293717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Series N |
E438176
|
entity |
| Predicate | hasTypeOfDocument |
P16808
|
FINISHED |
| Object | recommendation |
—
|
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: recommendation | Statement: [Series N, hasTypeOfDocument, recommendation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfDocument Context triple: [Series N, hasTypeOfDocument, recommendation]
-
A.
hasOfficialDocument
Indicates that an entity possesses or is associated with a formal, authorized document issued by a recognized authority.
-
B.
haveType
chosen
Indicates that an entity belongs to or is classified under a specified type or category.
-
C.
documentTypeIncluded
Indicates that a particular document type is contained within, or is part of, a specified set or collection of document types.
-
D.
documentTypeUsed
Indicates that a particular type or category of document is employed or applied in a given context or activity.
-
E.
hasTypeOfCase
Indicates that an entity is associated with or classified under a particular type or category of case.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5010205bc8190a32fe731ead3d988 |
completed | April 19, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.