Triple
T1103727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leqembi |
E25439
|
entity |
| Predicate | hasATCClass |
P23165
|
FINISHED |
| Object | N06DX |
—
|
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: N06DX | Statement: [Leqembi, hasATCClass, N06DX]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasATCClass Context triple: [Leqembi, hasATCClass, N06DX]
-
A.
hasAirportClassification
Indicates that an airport is assigned a specific classification or category based on defined criteria.
-
B.
hasLCClassification
Indicates that an entity is assigned a specific Library of Congress Classification code representing its subject or shelving category.
-
C.
UICClassification
Indicates the standardized classification or coding assigned to an entity according to the UIC (International Union of Railways) system.
-
D.
associatedVehicleWeightClass
Indicates the weight classification category that is linked or assigned to a particular vehicle.
-
E.
hasCargoDivision
Indicates that an organization possesses a specific division or unit responsible for cargo-related operations or services.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c375848190baec4d534f489616 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b7472c848190b0643872f67084a2 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:43 p.m.