Triple
T24598413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benbow |
E608745
|
entity |
| Predicate | hasThermalAnomalies |
P39404
|
FINISHED |
| Object | strong |
—
|
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: strong | Statement: [Benbow, hasThermalAnomalies, strong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThermalAnomalies Context triple: [Benbow, hasThermalAnomalies, strong]
-
A.
hasThermalActivity
chosen
Indicates that an entity exhibits or is associated with heat-related phenomena such as heating, cooling, or temperature change.
-
B.
hasThermalCharacteristic
Indicates that an entity possesses a specific thermal property or behavior, such as conductivity, capacity, or response to temperature.
-
C.
usesThermals
Indicates that one entity relies on rising warm air currents (thermals) as a means to gain lift, move, or maintain altitude.
-
D.
hasThermalResource
Indicates that an entity possesses, provides, or is associated with a source of thermal energy or heat-related capability.
-
E.
hasAnomaly
Indicates that an entity exhibits, contains, or is associated with an irregular, abnormal, or unexpected condition or feature.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.