Triple
T712178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siemens S70 |
E14233
|
entity |
| Predicate | typicalWidth |
P19786
|
FINISHED |
| Object | approximately 2.65 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: approximately 2.65 meters | Statement: [Siemens S70, typicalWidth, approximately 2.65 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWidth Context triple: [Siemens S70, typicalWidth, approximately 2.65 meters]
-
A.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
B.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
C.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
D.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
E.
minimumWidth
Indicates that there is a specified smallest allowable or required width for something in the relationship.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a77fcc6881908a025bb21e44ad56 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f221b081909fbaa689fb20eb3e |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a77e42e081909a6f2d1bfdc78ef0 |
completed | March 1, 2026, 8:54 p.m. |
Created at: March 1, 2026, 7:36 p.m.