Triple
T16795670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arctogadus glacialis |
E408223
|
entity |
| Predicate | hasAntifreezeProteins |
P124661
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Arctogadus glacialis, hasAntifreezeProteins, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAntifreezeProteins Context triple: [Arctogadus glacialis, hasAntifreezeProteins, true]
-
A.
hasTypicalFreezingPoint
Indicates the temperature at which a substance normally changes from liquid to solid under standard conditions.
-
B.
hasFrozenInWinter
Indicates that something becomes or has become frozen during the winter season.
-
C.
hasAquaticAdaptationsIn
Indicates that an entity possesses physical or behavioral adaptations suited for living or functioning in a specified aquatic environment.
-
D.
hasPermafrost
Indicates that a location or area contains ground that remains continuously frozen (permafrost) for an extended period.
-
E.
hasIcebergs
Indicates that one entity (typically a body of water or region) contains or is characterized by the presence of icebergs.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a96d888190a9876c3784bb7f95 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.