Triple
T10990954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maple |
E259752
|
entity |
| Predicate | programmingLanguage |
P1592
|
FINISHED |
| Object | Maple language |
E259752
|
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: Maple language | Statement: [Maple, programmingLanguage, Maple language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maple language Context triple: [Maple, programmingLanguage, Maple language]
-
A.
Maple
chosen
Maple is a comprehensive computer algebra system used for symbolic and numeric mathematics, modeling, and technical computing across education and research.
-
B.
Pear language
Pear language is an Austroasiatic language of the Pearic branch spoken by the Pear people of Cambodia and considered highly endangered.
-
C.
Mono language
Mono language is a Native American Uto-Aztecan language traditionally spoken by the Mono people of eastern California.
-
D.
Eiffel programming language
Eiffel is an object-oriented programming language designed by Bertrand Meyer that emphasizes software correctness through features like Design by Contract and strong support for modular, reusable code.
-
E.
Maple Library
Maple Library is a public community library serving residents of the Maple neighbourhood in Vaughan, Ontario.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d787b8d7088190b7d6b63c3bac4ad1 |
completed | April 9, 2026, 11:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e34504ebec8190a78e4795765b0c24 |
completed | April 18, 2026, 8:47 a.m. |
Created at: April 8, 2026, 9:24 p.m.