Triple
T262980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Furniture City |
E5790
|
entity |
| Predicate | associatedProduct |
P3585
|
FINISHED |
| Object | wooden furniture |
—
|
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: wooden furniture | Statement: [Furniture City, associatedProduct, wooden furniture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedProduct Context triple: [Furniture City, associatedProduct, wooden furniture]
-
A.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
B.
hasProduct
chosen
Indicates that an entity possesses, offers, or is associated with a particular product.
-
C.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
D.
primaryProduct
Indicates that one entity is the main or most important product associated with, produced by, or offered by another entity.
-
E.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
- 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_69a258dd8ea08190ac554a1cc8dfd8c3 |
completed | Feb. 28, 2026, 2:54 a.m. |
| NER | Named-entity recognition | batch_69a25d8c7f448190af9145256f994177 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6e07748190834022a65ba6d803 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.