Triple
T1996610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nile tilapia |
E43373
|
entity |
| Predicate | salinityTolerance |
P24238
|
FINISHED |
| Object | low to moderate salinity |
—
|
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: low to moderate salinity | Statement: [Nile tilapia, salinityTolerance, low to moderate salinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: salinityTolerance Context triple: [Nile tilapia, salinityTolerance, low to moderate salinity]
-
A.
salinityPreference
Indicates the preferred range or level of salinity under which an entity most optimally exists, functions, or occurs.
-
B.
hasSalinityRange
Indicates the range of salinity values within which something (such as a substance, environment, or organism) is present, applicable, or able to function.
-
C.
salinity
Indicates the concentration of dissolved salts present in or affecting something, typically a body of water or environment.
-
D.
saltTolerance
chosen
Indicates the degree to which an entity can withstand or function under saline (high-salt) conditions.
-
E.
salinityGradient
Indicates a relationship where the salinity of a medium changes in magnitude across space or depth between two locations or regions.
- 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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb91055d88190a980e7b42e5895d4 |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb79c97d48190b3147430ed39faa9 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.