Triple
T6935399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Group of the Cross |
E160540
|
entity |
| Predicate | writingSystem |
P454
|
FINISHED |
| Object | Maya script |
E153782
|
NE 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: Maya script | Statement: [Group of the Cross, writingSystem, Maya script]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maya script Context triple: [Group of the Cross, writingSystem, Maya script]
-
A.
Maya script
chosen
Maya script is the complex logosyllabic writing system of the ancient Maya, used to record their history, rituals, astronomy, and royal lineages on monuments, codices, and artifacts.
-
B.
Autodesk Maya
Autodesk Maya is a professional 3D computer graphics application widely used in film, television, and game development for modeling, animation, simulation, and rendering.
-
C.
NewtonScript
NewtonScript is an object-oriented, prototype-based programming language developed by Apple for its Newton PDA platform, designed for ease of use in pen-based and mobile applications.
-
D.
BrainScript
BrainScript is a domain-specific scripting language developed for defining and training neural networks within the Microsoft Cognitive Toolkit (CNTK).
-
E.
Mayavi
Mayavi is a 3D scientific data visualization library for Python, widely used for interactive plotting and analysis of complex numerical data.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6884e15208190b9e91487eaafcf85 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da429b5c8190a59901e0005a5415 |
completed | March 27, 2026, 7:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c75151d5e48190b2389ae9049d1454 |
completed | March 28, 2026, 3:56 a.m. |
Created at: March 27, 2026, 2:27 p.m.