Triple
T29873501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portuguese pavement |
E758655
|
entity |
| Predicate | sometimesUsesMaterial |
P1272
|
FINISHED |
| Object | basalt |
—
|
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: basalt | Statement: [Portuguese pavement, sometimesUsesMaterial, basalt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sometimesUsesMaterial Context triple: [Portuguese pavement, sometimesUsesMaterial, basalt]
-
A.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
B.
usesSupportMaterial
Indicates that an entity relies on or incorporates additional supporting materials or resources to carry out an action or fulfill a function.
-
C.
usesMaterialBy
Indicates that one entity makes use of or employs a material that is provided, specified, or created by another entity.
-
D.
isMaterialSpecific
Indicates that a relationship, rule, or property applies only to a particular material or set of materials, rather than being generally applicable.
-
E.
testedMaterial
Indicates that an entity has been used as the material or substance on which a test or experiment was performed.
- 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f676c7a4fc8190a980f9bc778a6043 |
completed | May 2, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:54 p.m.