Triple
T33566905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North American Datum of 1927 |
E859783
|
entity |
| Predicate | coordinateDifferencesMagnitude |
P27195
|
FINISHED |
| Object | tens of meters |
—
|
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: tens of meters | Statement: [North American Datum of 1927, coordinateDifferencesMagnitude, tens of meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coordinateDifferencesMagnitude Context triple: [North American Datum of 1927, coordinateDifferencesMagnitude, tens of meters]
-
A.
pointDifference
Indicates the numerical difference in points or scores between two compared entities.
-
B.
coordinateDifferencesRelativeTo
Indicates how the differences between coordinates of one entity are expressed or measured relative to the coordinate system or reference frame of another entity.
-
C.
distanceMetric
chosen
Indicates a quantitative measure of how far apart two entities are within a given space or according to a specified metric.
-
D.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
-
E.
minimumDistanceFormula
Indicates the mathematical expression used to compute the smallest possible distance between specified entities or geometric objects.
- 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_69f3497c1d288190a844ea699914e038 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: May 1, 2026, 1:40 a.m.