Triple
T30030135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFS Convention |
E762991
|
entity |
| Predicate | targetsSubstance |
P42606
|
FINISHED |
| Object | organotin compounds |
—
|
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: organotin compounds | Statement: [AFS Convention, targetsSubstance, organotin compounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsSubstance Context triple: [AFS Convention, targetsSubstance, organotin compounds]
-
A.
usedSubstance
Indicates that an entity has consumed, applied, or otherwise made use of a particular substance.
-
B.
associatedWithSubstance
chosen
Indicates that one entity has a relevant connection or involvement with a particular substance, such as use, presence, exposure, or composition.
-
C.
acceptsSubstance
Indicates that an entity receives, takes in, or allows the use of a specified substance.
-
D.
primarySubstanceExample
Indicates that one entity serves as the main illustrative example of a particular substance associated with another entity.
-
E.
secondarySubstanceExample
Indicates that one substance serves as a secondary or supporting example in relation to another primary substance or context.
- 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_69f2246ee6e48190b69e837b913b398a |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: April 29, 2026, 6:49 p.m.