Triple
T23908795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ITER project |
E601277
|
entity |
| Predicate | designedMinorRadius |
P85716
|
FINISHED |
| Object | about 2 metres |
—
|
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: about 2 metres | Statement: [ITER project, designedMinorRadius, about 2 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedMinorRadius Context triple: [ITER project, designedMinorRadius, about 2 metres]
-
A.
diameterMini
Indicates that one entity is the minimum diameter measurement associated with another entity.
-
B.
minimumRadiusOfCurves
Indicates the smallest allowable radius for any curve in a path, track, or route associated with the subject.
-
C.
minorSector
Indicates that one sector is a subordinate or less significant subdivision within a larger, primary sector.
-
D.
smallerDiscDiameter
Indicates that one disc has a smaller diameter than another disc in the relationship.
-
E.
curveRadius
chosen
Indicates the radius of curvature associated with an object or path, describing how sharply it bends at a given point.
- 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ce92e7688190ac421570e0d6a942 |
completed | April 29, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:37 p.m.