Triple
T14916311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Womb Chair |
E371390
|
entity |
| Predicate | hasCushionType |
P116661
|
FINISHED |
| Object | loose cushions |
—
|
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: loose cushions | Statement: [Womb Chair, hasCushionType, loose cushions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCushionType Context triple: [Womb Chair, hasCushionType, loose cushions]
-
A.
hasSeatMaterial
Indicates that an entity’s seat is made of, or covered with, a specified material.
-
B.
hasBackrestType
Indicates the specific kind or style of backrest that an object (typically a seat or chair) possesses.
-
C.
hasBedType
Indicates that an entity (such as a room or accommodation) is associated with a specific type or configuration of bed.
-
D.
hasInsoleType
Indicates that an item, typically footwear, possesses a specific type or category of insole.
-
E.
hasBedMaterial
Indicates that one entity has, contains, or is characterized by a particular bed material (e.g., the substance forming the base or bedding of that 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded62038508190946499cd3552990e |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:31 a.m.