Triple
T5110900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hermione Granger |
E115210
|
entity |
| Predicate | bestSubject |
P61630
|
FINISHED |
| Object | Charms |
—
|
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: Charms | Statement: [Hermione Granger, bestSubject, Charms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestSubject Context triple: [Hermione Granger, bestSubject, Charms]
-
A.
bestOf
Indicates that one entity is the top-ranked or most outstanding member within a specified group, set, or collection.
-
B.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
C.
subjectCanBe
Indicates that the subject has the potential or capability to assume, become, or be classified as the specified object or state.
-
D.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
-
E.
hasPrimarySubject
Indicates that an entity is the main or principal subject associated with another entity or resource.
- F. None of above. chosen
Provenance (4 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ad362c8190b9cbded390aaea3c |
completed | March 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd72e1b7cc8190b2e621fdf8f22e38 |
completed | March 20, 2026, 4:16 p.m. |
Created at: March 20, 2026, 1:41 p.m.