Triple
T17262053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | congenital Zika syndrome |
E419030
|
entity |
| Predicate | firstRecognizedDuring |
P123477
|
FINISHED |
| Object | Zika virus outbreak in Brazil |
—
|
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: Zika virus outbreak in Brazil | Statement: [congenital Zika syndrome, firstRecognizedDuring, Zika virus outbreak in Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstRecognizedDuring Context triple: [congenital Zika syndrome, firstRecognizedDuring, Zika virus outbreak in Brazil]
-
A.
recognizableWhen
Indicates that one entity can be correctly identified or distinguished under the conditions, context, or representation specified by another entity.
-
B.
recognizedFirstBy
Indicates that one entity was the earliest or initial recognizer, identifier, or acknowledger of another entity.
-
C.
firstClearlyRecognizedIn
chosen
Indicates the point in time or context when something was first clearly identified, acknowledged, or distinguished as such.
-
D.
wasRecognizedAs
Indicates that an entity was formally identified, acknowledged, or designated as having a particular role, status, or quality.
-
E.
firstSignalReceivedDate
Indicates the date on which an entity first received a particular signal.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e717a348190ae6835fb08f38125 |
completed | April 19, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69e3832a284481908a8a3da7ac91de5a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.