Triple
T23278367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ailanthus altissima |
E588784
|
entity |
| Predicate | ailanthoneEffect |
P58407
|
FINISHED |
| Object | inhibits growth of other plants |
—
|
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: inhibits growth of other plants | Statement: [Ailanthus altissima, ailanthoneEffect, inhibits growth of other plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ailanthoneEffect Context triple: [Ailanthus altissima, ailanthoneEffect, inhibits growth of other plants]
-
A.
alkaloidType
Indicates that one entity is classified as a specific type or category of alkaloid in relation to another entity.
-
B.
lionTincture
Indicates a heraldic relationship where a lion is depicted in a specific color or pattern (tincture) on a coat of arms or shield.
-
C.
mechanismOfActionStudied
Indicates that the relationship involves examining or investigating how an action, intervention, or agent produces its effects or outcomes.
-
D.
hasPharmacologicalEffect
chosen
Indicates that one entity produces a specific pharmacological effect or action on another entity.
-
E.
containsAlkaloids
Indicates that a substance, organism, or material has alkaloid compounds present within it.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1957991108190ac82fa6dd355f722 |
completed | April 29, 2026, 5:22 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:49 p.m.