Triple
T4200544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2015–2016 Zika virus outbreak |
E86053
|
entity |
| Predicate | secondaryTransmissionRoute |
P54323
|
FINISHED |
| Object | sexual transmission |
—
|
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: sexual transmission | Statement: [2015–2016 Zika virus outbreak, secondaryTransmissionRoute, sexual transmission]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryTransmissionRoute Context triple: [2015–2016 Zika virus outbreak, secondaryTransmissionRoute, sexual transmission]
-
A.
secondaryHub
Indicates that an entity functions as a secondary or backup hub in relation to a primary hub within a network or system.
-
B.
secondaryTo
Indicates that one condition, event, or factor occurs as a consequence of, or is caused by, another primary condition, event, or factor.
-
C.
secondaryTarget
Indicates that an entity serves as an additional or subordinate target in relation to a primary target within a given context or action.
-
D.
secondStation
Indicates that one station in a sequence or route is the second station relative to another reference point or ordering.
-
E.
laterTransmission
Indicates that one transmission event occurs after another in time.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0363bbb8819093f396afe91972e2 |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af01959c4881909eb1adcb3bdadbe6 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af02e4e2308190b527e3b78eb8fa71 |
completed | March 9, 2026, 5:27 p.m. |
Created at: March 9, 2026, 3:49 p.m.