Triple
T28283197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hara forests of Qeshm |
E713208
|
entity |
| Predicate | salinityAdaptation |
P102995
|
FINISHED |
| Object | salt-tolerant vegetation |
—
|
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: salt-tolerant vegetation | Statement: [Hara forests of Qeshm, salinityAdaptation, salt-tolerant vegetation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: salinityAdaptation Context triple: [Hara forests of Qeshm, salinityAdaptation, salt-tolerant vegetation]
-
A.
salinityAdaptationMechanism
chosen
Indicates the mechanism by which an entity adjusts or responds to varying salinity levels in its environment.
-
B.
salinityPreference
Indicates the preferred range or level of salinity under which an entity most optimally exists, functions, or occurs.
-
C.
salinityRegime
Indicates the pattern or level of salt concentration characterizing an environment or system over time.
-
D.
salinity
Indicates the concentration of dissolved salts present in or affecting something, typically a body of water or environment.
-
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_69efb52275788190ae5181ccebef18ce |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6447df07c8190bbbd284a8386c02e |
completed | May 2, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:24 p.m.