Triple
T33588955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subtropical Front (South Indian Ocean) |
E860364
|
entity |
| Predicate | hasTemporalVariabilityIn |
P195055
|
FINISHED |
| Object | latitude |
—
|
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: latitude | Statement: [Subtropical Front (South Indian Ocean), hasTemporalVariabilityIn, latitude]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporalVariabilityIn Context triple: [Subtropical Front (South Indian Ocean), hasTemporalVariabilityIn, latitude]
-
A.
hasVariability
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
-
B.
variesOver
Indicates that the value, state, or behavior of one entity changes as a function of another entity or parameter.
-
C.
hasTypicalTemperatureVariation
Indicates that an entity is associated with a characteristic or usual range of temperature change under normal conditions.
-
D.
hasCauseOfVariability
Indicates a relationship where one factor or condition is identified as the source or driver of variation observed in another.
-
E.
hasSpectralVariability
Indicates that an entity exhibits changes or fluctuations in its spectral properties over time or under different conditions.
- 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
| PDg | Predicate description generation | batch_69fd9fef7aac819089cc88dd3d00296d |
completed | May 8, 2026, 8:33 a.m. |
Created at: May 1, 2026, 1:40 a.m.