Triple
T8245198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nylon |
E192833
|
entity |
| Predicate | wasFirstUsedCommerciallyFor |
P1929
|
FINISHED |
| Object | toothbrush bristles |
—
|
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: toothbrush bristles | Statement: [Nylon, wasFirstUsedCommerciallyFor, toothbrush bristles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasFirstUsedCommerciallyFor Context triple: [Nylon, wasFirstUsedCommerciallyFor, toothbrush bristles]
-
A.
firstCommercialUse
chosen
Indicates the earliest point in time at which something was used commercially or put into commercial operation.
-
B.
firstWidelyUsedFor
Indicates that something was the earliest instance to be broadly adopted or commonly used for a particular purpose or application.
-
C.
firstUsedFor
Indicates that one entity was the earliest or original thing for which another entity was used or applied.
-
D.
firstHistoricalUse
Indicates that the subject entity represents the earliest known or recorded instance of the object entity being used or occurring in history.
-
E.
locationOfFirstCommercialUse
Indicates the place where something was first used commercially.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7872f6d481909ea1d3c2aad1a2b1 |
completed | March 31, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:48 p.m.