Triple
T17093051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taï Forest ebolavirus |
E414770
|
entity |
| Predicate | indexPatientExposure |
P125870
|
FINISHED |
| Object | necropsy of infected chimpanzee |
—
|
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: necropsy of infected chimpanzee | Statement: [Taï Forest ebolavirus, indexPatientExposure, necropsy of infected chimpanzee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: indexPatientExposure Context triple: [Taï Forest ebolavirus, indexPatientExposure, necropsy of infected chimpanzee]
-
A.
numberOfAnnualPatientVisits
Indicates the total count of patient visits that occur over the course of one year.
-
B.
encounterLocation
Indicates the place or setting where two or more entities meet, interact, or come into contact.
-
C.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
D.
scopeOfVisits
Indicates the range, extent, or boundaries within which visits or visiting activities occur or are applicable.
-
E.
hasPatientRole
Indicates that an entity participates in a relationship or activity specifically in the role of a patient (the one receiving care, treatment, or action).
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbfabf548190a0d37bab3d4ef2fa |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d67b14481909fcdbdeaa5c34785 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:35 a.m.