Triple
T17052246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inuit Tapiriit Kanatami |
E413725
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
ITK
ITK is the national Inuit organization in Canada that represents and advocates for Inuit rights and interests at the federal level.
|
E1248484
|
NE FINISHED |
How this triple was built (4 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: ITK | Statement: [Inuit Tapiriit Kanatami, shortName, ITK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ITK Context triple: [Inuit Tapiriit Kanatami, shortName, ITK]
-
A.
Kitware
Kitware is a software research and development company best known for creating open-source tools and platforms for scientific computing, visualization, and software build management.
-
B.
scikit-image
scikit-image is an open-source Python library that provides a wide range of image processing and computer vision algorithms built on top of NumPy and SciPy.
-
C.
OpenCV
OpenCV is a widely used open-source computer vision and machine learning library that provides tools for real-time image and video processing across multiple platforms.
-
D.
ImageWorks
ImageWorks is an interactive, hands-on exhibit area at Epcot where guests explore creativity and imagination through playful digital and sensory experiences.
-
E.
OSG
OSG is the abbreviated name commonly used to refer to the Office of the Secretary-General.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: ITK Triple: [Inuit Tapiriit Kanatami, shortName, ITK]
Generated description
ITK is the national Inuit organization in Canada that represents and advocates for Inuit rights and interests at the federal level.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ITK Target entity description: ITK is the national Inuit organization in Canada that represents and advocates for Inuit rights and interests at the federal level.
-
A.
Kitware
Kitware is a software research and development company best known for creating open-source tools and platforms for scientific computing, visualization, and software build management.
-
B.
scikit-image
scikit-image is an open-source Python library that provides a wide range of image processing and computer vision algorithms built on top of NumPy and SciPy.
-
C.
OpenCV
OpenCV is a widely used open-source computer vision and machine learning library that provides tools for real-time image and video processing across multiple platforms.
-
D.
ImageWorks
ImageWorks is an interactive, hands-on exhibit area at Epcot where guests explore creativity and imagination through playful digital and sensory experiences.
-
E.
OSG
OSG is the abbreviated name commonly used to refer to the Office of the Secretary-General.
- F. None of above. chosen
Provenance (5 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa3324881908d9e445ba1cfe109 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012343eca0819086a07511c5d22878 |
completed | May 11, 2026, 12:31 a.m. |
| NEDg | Description generation | batch_6a012585a1548190a112f55e2d84ccac |
completed | May 11, 2026, 12:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0126536c348190b9b2eadb4969f8c2 |
completed | May 11, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:34 a.m.