Triple
T23293440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hypoxylon |
E590095
|
entity |
| Predicate | impactOnWood |
P1357
|
FINISHED |
| Object | causes soft rot and discoloration |
—
|
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: causes soft rot and discoloration | Statement: [Hypoxylon, impactOnWood, causes soft rot and discoloration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnWood Context triple: [Hypoxylon, impactOnWood, causes soft rot and discoloration]
-
A.
hasWood
Indicates that one entity possesses, contains, or is made of wood in relation to another entity or context.
-
B.
topWood
Indicates that one entity is made of or features a particular type of wood used specifically for its top surface or top section.
-
C.
woodProperty
chosen
Indicates that one entity specifies or characterizes a property or attribute of wood associated with another entity.
-
D.
windImpact
Indicates the influence or effect that wind has on an entity, condition, or process.
-
E.
isWoodenStructure
Indicates that the subject is a structure primarily made of wood or constructed using wooden components.
- 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_69e25d1af9d88190a0b9b5e8fa608618 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196ccd9b481909ab5d3504640025e |
completed | April 29, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:02 p.m.