Triple
T18238150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natural History |
E436734
|
entity |
| Predicate | primaryTopics |
P96519
|
FINISHED |
| Object | biology |
—
|
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: biology | Statement: [Natural History, primaryTopics, biology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTopics Context triple: [Natural History, primaryTopics, biology]
-
A.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
B.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
-
C.
primarySubjectArea
chosen
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
-
D.
primaryConcept
Indicates that one concept is the main or central idea in relation to another concept or context.
-
E.
primaryIssue
Indicates that the related item is the main or most important issue among a set of issues.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e0a0ac819090d48ae45b1ebfc9 |
completed | April 19, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69e4332336cc8190808b9c70c888ba65 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:33 a.m.