Triple
T9712487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Engrampa |
E235052
|
entity |
| Predicate | supportsDesktopEnvironment |
P32775
|
FINISHED |
| Object | MATE |
E192874
|
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: MATE | Statement: [Engrampa, supportsDesktopEnvironment, MATE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MATE Context triple: [Engrampa, supportsDesktopEnvironment, MATE]
-
A.
MATE
chosen
MATE is a lightweight, traditional-style desktop environment for Unix-like operating systems, derived from GNOME 2 and focused on simplicity and low resource usage.
-
B.
Eye of MATE
Eye of MATE is the official image viewer application for the MATE desktop environment, designed for simple and efficient viewing of image files.
-
C.
MAT
MAT is the commonly used abbreviation for the Moscow Art Theatre, a historic and influential Russian theatre company renowned for its pioneering work in modern drama and acting techniques.
-
D.
Matemale
Matemale is a small commune in the Pyrénées-Orientales department of southern France, known for its high-altitude lake and mountain setting in the Capcir plateau.
-
E.
NaMATA
NaMATA is the metropolitan transport authority responsible for planning and coordinating public transport systems in the Nairobi metropolitan area.
- 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_69ca84cd8fa0819090a5e243ceb37003 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e0705f8819095852263009c28c5 |
completed | April 1, 2026, 10:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19f8c26dc8190a6fa21bde27ba6fa |
completed | April 4, 2026, 11:32 p.m. |
Created at: March 30, 2026, 8:19 p.m.