Triple
T14300093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Craftsman furniture |
E354538
|
entity |
| Predicate | typicalJoinery |
P113674
|
FINISHED |
| Object | mortise-and-tenon joints |
—
|
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: mortise-and-tenon joints | Statement: [Craftsman furniture, typicalJoinery, mortise-and-tenon joints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalJoinery Context triple: [Craftsman furniture, typicalJoinery, mortise-and-tenon joints]
-
A.
typicalFinish
Indicates that an action, process, or event commonly or characteristically ends with a particular outcome or state.
-
B.
furniture
Indicates that one entity is a piece of furniture associated with, located in, or used by another entity.
-
C.
furnishingType
Indicates the type or category of furnishings associated with an entity, such as a property or room.
-
D.
hasDoorMaterial
Indicates that an entity’s door is made of, or primarily composed of, a specified material.
-
E.
woodProperty
Indicates that one entity specifies or characterizes a property or attribute of wood associated with another entity.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717e246c819083e67ac2b3b77881 |
completed | April 14, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:11 a.m.