Triple
T4304832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vitaceae |
E99928
|
entity |
| Predicate | notableCrop |
P55351
|
FINISHED |
| Object | grapes |
—
|
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: grapes | Statement: [Vitaceae, notableCrop, grapes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCrop Context triple: [Vitaceae, notableCrop, grapes]
-
A.
notableTrim
Indicates that an entity has a particularly significant or distinguished trim level or decorative variant compared to standard versions.
-
B.
notableField
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
-
C.
notableCover
Indicates that one entity is a particularly well-known or significant cover version or adaptation of another entity.
-
D.
notableSingle
Indicates that the subject is particularly recognized or distinguished for one specific, individual instance (such as a single work, event, or achievement).
-
E.
notableColor
Indicates that an entity is characteristically or prominently associated with a particular color.
- F. None of above. chosen
Provenance (4 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350b8e1cc819094ce3d6f6c8da767 |
completed | March 12, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69b347ff45cc8190b0cc335a94cc3d73 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:09 p.m.