Triple
T26521763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Institutional Animal Care and Use Committee |
E669974
|
entity |
| Predicate | reviewsDocumentType |
P19006
|
FINISHED |
| Object | animal use protocol |
—
|
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: animal use protocol | Statement: [Institutional Animal Care and Use Committee, reviewsDocumentType, animal use protocol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reviewsDocumentType Context triple: [Institutional Animal Care and Use Committee, reviewsDocumentType, animal use protocol]
-
A.
reviewType
Indicates the specific category or kind of review associated with an item, action, or relationship.
-
B.
reviewFormat
Indicates the specific structure, style, or medium in which a review is presented or delivered.
-
C.
reviewAggregator
Indicates that an entity functions as a collector and summarizer of reviews or ratings about other entities.
-
D.
reviewModel
Indicates that an entity evaluates, critiques, or assesses another entity according to a particular standard or criteria.
-
E.
documentationType
chosen
Indicates the specific category or kind of documentation associated with or required for an entity or process.
- 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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620debeb48190b7db395fb86cf8d9 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 1:28 a.m.