Triple
T20381295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Academy of Medicine |
E497833
|
entity |
| Predicate | hasTaxonomyTag |
P139904
|
FINISHED |
| Object | medical academy |
—
|
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: medical academy | Statement: [New York Academy of Medicine, hasTaxonomyTag, medical academy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTaxonomyTag Context triple: [New York Academy of Medicine, hasTaxonomyTag, medical academy]
-
A.
hasTaggingSystem
Indicates that an entity is associated with or supports a system for assigning and managing tags or labels.
-
B.
hasTagmata
Indicates that an organism possesses distinct functional body regions (tagmata) into which its body is divided.
-
C.
hasClassifiedTaxon
Indicates that an entity has assigned or associated a specific taxonomic classification to another entity.
-
D.
includesTaxaWith
Indicates that an entity contains or encompasses one or more specified taxa within its scope or membership.
-
E.
hasFacet
Indicates that an entity possesses a particular aspect, side, or dimension as one of its distinguishable parts or characteristics.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678b0ee708190bdbe4aab28a61525 |
completed | April 20, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:27 a.m.