Triple
T20757583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gelsemiaceae |
E510887
|
entity |
| Predicate | toxicComponentLocation |
P96471
|
FINISHED |
| Object | all plant parts in many species |
—
|
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: all plant parts in many species | Statement: [Gelsemiaceae, toxicComponentLocation, all plant parts in many species]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toxicComponentLocation Context triple: [Gelsemiaceae, toxicComponentLocation, all plant parts in many species]
-
A.
toxinLocation
chosen
Indicates the place or environment where a toxin is present, stored, or exerts its effect.
-
B.
toxicPart
Indicates that one entity is a component or portion of another that is harmful, poisonous, or otherwise toxic.
-
C.
toxicTo
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
-
D.
toxinType
Indicates the specific kind or category of toxin associated with an entity.
-
E.
conflictLocation
Indicates the place or geographic area where a conflict, dispute, or confrontation occurs or is centered.
- 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c23113c88190a567c3a098cf7552 |
completed | April 21, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:35 p.m.