Triple
T9292892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalí Triangle |
E223562
|
entity |
| Predicate | approximateDistanceBetweenSites |
P22795
|
FINISHED |
| Object | tens of kilometers |
—
|
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 kilometers | Statement: [Dalí Triangle, approximateDistanceBetweenSites, tens of kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDistanceBetweenSites Context triple: [Dalí Triangle, approximateDistanceBetweenSites, tens of kilometers]
-
A.
approximateDistanceFrom
Indicates an estimated or rough measure of how far one entity is from another.
-
B.
approximateDistanceKm
chosen
Indicates the estimated distance between two entities measured in kilometers, typically with some degree of inaccuracy or approximation.
-
C.
approximateRouteLength
Indicates the estimated total distance or length of a given route, rather than its exact measured value.
-
D.
hasApproximateDistanceScale
Indicates that one entity is related to another by a distance measure that is approximate or estimated rather than exact.
-
E.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
- 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_69ca8422ddf881908a3f8f876c9f53aa |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0898b3288190a627a58bfd9c57fe |
completed | April 1, 2026, 11:59 a.m. |
| PD | Predicate disambiguation | batch_69cc7a5aeb748190afb89c6bbd2a6d6f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:35 p.m.