Triple
T6801761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archimedean screw |
E156202
|
entity |
| Predicate | hasCrossSection |
P73088
|
FINISHED |
| Object | cylindrical |
—
|
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: cylindrical | Statement: [Archimedean screw, hasCrossSection, cylindrical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossSection Context triple: [Archimedean screw, hasCrossSection, cylindrical]
-
A.
crossesSectionOf
Indicates that one entity passes through or over a specific segment or portion of another entity.
-
B.
hasCross
Indicates that one entity possesses, displays, or is marked by a cross in relation to another entity or context.
-
C.
hasSurfaceSections
Indicates that an entity is composed of or divided into distinct sections or parts of its surface.
-
D.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
E.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
- 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_69c68826e6a48190a3d220b541e639de |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2e595188190a0bb4b595df3adb2 |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d2a8f9188190abbb8c730e7b5edf |
completed | March 27, 2026, 6:55 p.m. |
Created at: March 27, 2026, 2:16 p.m.