Triple
T7771087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagaswaram |
E179069
|
entity |
| Predicate | isOftenMadeOf |
P1272
|
FINISHED |
| Object | aacha (hardwood) |
—
|
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: aacha (hardwood) | Statement: [Nagaswaram, isOftenMadeOf, aacha (hardwood)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenMadeOf Context triple: [Nagaswaram, isOftenMadeOf, aacha (hardwood)]
-
A.
madeWith
Indicates that one entity is created, produced, or constructed using another entity as a material, ingredient, or component.
-
B.
materialFormedIn
Indicates that a material is created, produced, or formed within a specified process, environment, or context.
-
C.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
D.
isFamouslyUsedIn
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
-
E.
madeBy
Indicates that something is created, produced, or brought into existence by a particular agent or source.
- 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c7045ebae88190a04c8f972795e615 |
completed | March 27, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69c7016f4ce881909c2e9f610255187b |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:11 p.m.