Triple
T36095396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sorna |
E1044044
|
entity |
| Predicate | typicallyMadeOf |
P1272
|
FINISHED |
| Object | wood |
—
|
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: wood | Statement: [sorna, typicallyMadeOf, wood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyMadeOf Context triple: [sorna, typicallyMadeOf, wood]
-
A.
materialFormedIn
Indicates that a material is created, produced, or formed within a specified process, environment, or context.
-
B.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
madeWith
Indicates that one entity is created, produced, or constructed using another entity as a material, ingredient, or component.
-
D.
chainMadeOf
Indicates that a chain is composed of, or constructed from, a specified material or substance.
-
E.
historicallyMadeOf
Indicates that something was typically or traditionally constructed from a particular material in the past, even if that may no longer be the case.
- 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_69f76e32d60c8190ba781ffaaab4aa3d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.