Triple
T11974107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nebbia v. New York |
E284993
|
entity |
| Predicate | productInvolved |
P25885
|
FINISHED |
| Object | milk |
—
|
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: milk | Statement: [Nebbia v. New York, productInvolved, milk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productInvolved Context triple: [Nebbia v. New York, productInvolved, milk]
-
A.
usesProduct
Indicates that one entity makes use of, applies, or employs a particular product.
-
B.
materialInvolved
chosen
Indicates that a particular material participates in, is used by, or is otherwise involved in the referenced process, event, or relationship.
-
C.
productIncludes
Indicates that a product contains, comprises, or is composed of the specified component, item, or feature.
-
D.
byProduct
Indicates that one entity is produced incidentally or as a secondary result of a process, activity, or creation involving another entity.
-
E.
productFor
Indicates that one entity is intended to be used by, with, or in relation to another entity as its product or offering.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9039107e48190ae4c4efd6257dd3c |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:46 p.m.