Triple
T6932298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mesoamerican Long Count calendar |
E160464
|
entity |
| Predicate | correlationConstant |
P9148
|
FINISHED |
| Object | GMT 584283 |
—
|
LITERAL 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: GMT 584283 | Statement: [Mesoamerican Long Count calendar, correlationConstant, GMT 584283]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correlationConstant Context triple: [Mesoamerican Long Count calendar, correlationConstant, GMT 584283]
-
A.
relatedConstant
Indicates that one entity is a fixed, unchanging value or constant that is associated with or linked to another entity.
-
B.
constant
Indicates that the relationship or value does not change across different instances, contexts, or over time.
-
C.
correlatorType
Indicates the specific kind or category of correlator used to establish or analyze a correlation between entities or signals.
-
D.
hasCouplingConstant
Indicates that one entity is associated with a specific coupling constant value that quantifies the strength of an interaction or relationship.
-
E.
usesConstant
chosen
Indicates that one entity makes use of a specific constant value defined or provided by another entity.
- 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_69c6884e15208190b9e91487eaafcf85 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da3fa7fc8190a03e7132871a9af4 |
completed | March 27, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bb577c81908ee8b415b4281f3d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:27 p.m.