Triple
T31897647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Louis Limestone |
E814327
|
entity |
| Predicate | bedding |
P99904
|
FINISHED |
| Object | thick-bedded to massive |
—
|
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: thick-bedded to massive | Statement: [St. Louis Limestone, bedding, thick-bedded to massive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bedding Context triple: [St. Louis Limestone, bedding, thick-bedded to massive]
-
A.
beddingCharacteristic
chosen
Indicates a relationship where a bedding item is associated with a specific property, feature, or quality it possesses.
-
B.
beds
Indicates that one entity provides or designates a place for another entity to sleep or rest.
-
C.
bedCover
Indicates that one object functions as a covering placed over a bed.
-
D.
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).
-
E.
hasBedType
Indicates that an entity (such as a room or accommodation) is associated with a specific type or configuration of bed.
- 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_69f348f04d7881909537fc9e7cbc670e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b165382c8190af1947dec907a015 |
completed | May 3, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 30, 2026, 11:59 p.m.