Triple
T2920999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kow-Ata underground lake |
E78722
|
entity |
| Predicate | hasWaterComposition |
P26020
|
FINISHED |
| Object | sulfur-rich |
—
|
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: sulfur-rich | Statement: [Kow-Ata underground lake, hasWaterComposition, sulfur-rich]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterComposition Context triple: [Kow-Ata underground lake, hasWaterComposition, sulfur-rich]
-
A.
hasHydrosphere
Indicates that an entity possesses or is characterized by a surrounding layer or system of water, such as oceans, seas, lakes, or other bodies of liquid water.
-
B.
waterContains
chosen
Indicates that a body or volume of water holds, includes, or has within it a specified substance, object, or entity.
-
C.
hasWaterBalance
Indicates that an entity maintains or exhibits a particular state or condition of water balance, such as hydration level or equilibrium between water intake and loss.
-
D.
hasWaterColor
Indicates that an entity possesses or is characterized by a particular color of water.
-
E.
hasWaterIce
Indicates that one entity contains, possesses, or is characterized by the presence of water in solid (ice) form.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:54 p.m.