Triple
T5795602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Georges Charpentier and Her Children |
E128500
|
entity |
| Predicate | hasDimensionUnit |
P28578
|
FINISHED |
| Object | centimetres |
—
|
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: centimetres | Statement: [Madame Georges Charpentier and Her Children, hasDimensionUnit, centimetres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDimensionUnit Context triple: [Madame Georges Charpentier and Her Children, hasDimensionUnit, centimetres]
-
A.
hasUnitOf
chosen
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
B.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
C.
hasIndividualDimension
Indicates that an entity possesses a specific, separately identifiable dimension or measurable extent as an individual attribute.
-
D.
hasDimensionality
Indicates that an entity possesses a specific number of dimensions or a particular dimensional structure.
-
E.
hasDimensionParameter
Indicates that an entity is associated with a specific dimensional parameter (such as size, length, width, or height) that characterizes its measurable extent.
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1304588190b59a18fb7b70a60f |
completed | March 22, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.