Triple
T8890657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kryptonite |
E211652
|
entity |
| Predicate | whiteKryptoniteEffect |
P85562
|
FINISHED |
| Object | kills plant life |
—
|
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: kills plant life | Statement: [Kryptonite, whiteKryptoniteEffect, kills plant life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: whiteKryptoniteEffect Context triple: [Kryptonite, whiteKryptoniteEffect, kills plant life]
-
A.
whitenEffect
Indicates that an entity causes or contributes to the whitening or lightening of another entity’s color or appearance.
-
B.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
C.
bladeColour
Indicates the color attribute assigned to a blade in the relationship.
-
D.
lanternColor
Indicates that one entity specifies or describes the color attribute of a lantern associated with another entity.
-
E.
workBlackAndWhite
Indicates that the work is presented in black and white rather than in 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_69ca83907954819096d52a245b635841 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc619188508190aacda410f0b4c98d |
completed | April 1, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5d6e54808190af4156edd4c8ffbc |
completed | March 31, 2026, 11:49 p.m. |
Created at: March 30, 2026, 6:53 p.m.