Triple
T6561214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya numerals |
E153785
|
entity |
| Predicate | maximumDotsPerPlace |
P71809
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Maya numerals, maximumDotsPerPlace, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumDotsPerPlace Context triple: [Maya numerals, maximumDotsPerPlace, 4]
-
A.
corePointsMaximum
Indicates the maximum number of core points that can be assigned, accumulated, or recognized within a given system or context.
-
B.
maximumStationsPerSegment
Indicates the greatest number of stations that are allowed or can exist within a single segment.
-
C.
maximumNumberOfSegments
Indicates the greatest allowable or observed count of discrete segments into which something can be or is divided.
-
D.
maximumReach
Indicates the greatest extent, distance, or limit that something can reach or influence within a given context.
-
E.
clusterDensity
Indicates the degree to which elements within a cluster are closely packed or concentrated relative to its size or volume.
- F. None of above. chosen
Provenance (4 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c1b15d3481908ae66e3d7564b352 |
completed | March 27, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c6acf6d4148190914b19e9affd8c76 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6c1b007148190b5164d6d09584cdf |
completed | March 27, 2026, 5:43 p.m. |
Created at: March 27, 2026, 1:52 p.m.