Triple
T2504127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mycobacterium tuberculosis |
E52537
|
entity |
| Predicate | primaryDisease |
P40194
|
FINISHED |
| Object | tuberculosis |
—
|
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: tuberculosis | Statement: [Mycobacterium tuberculosis, primaryDisease, tuberculosis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryDisease Context triple: [Mycobacterium tuberculosis, primaryDisease, tuberculosis]
-
A.
primaryType
Indicates the main or most fundamental category or classification assigned to an entity, distinguishing it from any secondary or auxiliary types.
-
B.
primaryPigment
Indicates that one pigment is the main or dominant colorant used or present in relation to another entity.
-
C.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
D.
primaryStatus
Indicates the main or most important status assigned to an entity among potentially multiple statuses.
-
E.
primaryInfectionStructure
Indicates the structure that serves as the main or initial means by which an infection is established in a host.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1cd2db0819087d21ec49ffd9585 |
completed | March 7, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69abd0bba5348190bb4637d3165cb339 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1aa13a08190a8757c017d8a2478 |
completed | March 7, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:46 p.m.