Triple
T22446334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ML language family |
E554871
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | MLton |
—
|
NE NERFINISHED |
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: MLton | Statement: [ML language family, hasMember, MLton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MLton Context triple: [ML language family, hasMember, MLton]
-
A.
MLton
chosen
MLton is a whole-program optimizing compiler for the Standard ML programming language, known for its aggressive optimizations and high-performance native code generation.
-
B.
Motl
Motl is the mischievous, sharp-witted young boy who narrates Sholem Aleichem’s classic Yiddish novel "Motl, Peysi the Cantor’s Son."
-
C.
Matalom
Matalom is a coastal municipality in the province of Leyte in the Philippines known for its beaches and rural communities.
-
D.
Met Mile
Met Mile is a prestigious one-mile Grade I Thoroughbred horse race held annually at Belmont Park in New York.
-
E.
Matalon
Matalon is a Hebrew-origin surname borne by various notable Israeli figures in literature, politics, and public life.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4803908190990280ebd258cb03 |
completed | April 29, 2026, 1:13 a.m. |
Created at: April 16, 2026, 8:47 p.m.