Triple
T23884386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GMT correlation |
E600288
|
entity |
| Predicate | mostWidelyUsedBy |
P40071
|
FINISHED |
| Object | Maya scholars |
—
|
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: Maya scholars | Statement: [GMT correlation, mostWidelyUsedBy, Maya scholars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostWidelyUsedBy Context triple: [GMT correlation, mostWidelyUsedBy, Maya scholars]
-
A.
isWidelyUsed
Indicates that something is commonly or extensively utilized across many contexts, users, or situations.
-
B.
isFamouslyUsedBy
Indicates that something is widely and notably used by a particular person, group, or entity, in a way that is broadly recognized or associated with them.
-
C.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
D.
primarilyUsedBy
chosen
Indicates that something is mainly or most commonly used by a particular entity or group.
-
E.
mostWidelyUsedImplementationOf
Indicates that one implementation of something is the most commonly or widely used version among all its implementations.
- F. None of above.
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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ccfbbe4c819093e590709719ab72 |
completed | April 29, 2026, 9:18 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:24 p.m.