Triple
T26205004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erythroxylum coca |
E655336
|
entity |
| Predicate | traditionalEffect |
P179456
|
FINISHED |
| Object | reduction of fatigue |
—
|
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: reduction of fatigue | Statement: [Erythroxylum coca, traditionalEffect, reduction of fatigue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalEffect Context triple: [Erythroxylum coca, traditionalEffect, reduction of fatigue]
-
A.
canonicalEffect
Indicates the standard or primary effect that an action, event, or entity is typically understood to produce.
-
B.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
C.
ultimateEffect
Indicates the final or overall outcome that results from a preceding action, condition, or sequence of events.
-
D.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
E.
temporaryEffect
Indicates that one entity causes or experiences an effect that is limited in duration and does not produce a lasting change.
- 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_69ee5b49adb4819086545280d4ef6337 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f722c1bc648190a79bfdc722dcaaa4 |
completed | May 3, 2026, 10:26 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f7221bc57c819085c1464a45e61b2f |
completed | May 3, 2026, 10:23 a.m. |
Created at: April 26, 2026, 8:50 p.m.