Triple
T16284863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guinea worm disease |
E395363
|
entity |
| Predicate | primarySymptom |
P122518
|
FINISHED |
| Object | painful skin blister |
—
|
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: painful skin blister | Statement: [Guinea worm disease, primarySymptom, painful skin blister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySymptom Context triple: [Guinea worm disease, primarySymptom, painful skin blister]
-
A.
primaryDisease
Indicates that a disease is the main or principal medical condition affecting an entity, as opposed to secondary or comorbid conditions.
-
B.
primaryIssue
Indicates that the related item is the main or most important issue among a set of issues.
-
C.
primarySin
Indicates a fundamental or chief moral wrongdoing attributed to an entity, often viewed as the root or most significant sin in a given context.
-
D.
primaryCatch
Indicates that an entity is the main or most significant target, recipient, or object captured or obtained in a given context.
-
E.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24913a55081909a9a5a7a7f4806cc |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:05 a.m.