Triple
T450409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anchorage |
E7113
|
entity |
| Predicate | averageJulyTemperatureC |
P5273
|
FINISHED |
| Object | approximately 15 |
—
|
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: approximately 15 | Statement: [Anchorage, averageJulyTemperatureC, approximately 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageJulyTemperatureC Context triple: [Anchorage, averageJulyTemperatureC, approximately 15]
-
A.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
B.
averageHighTemperatureInJuly
chosen
Indicates the typical or mean value of the highest daily temperatures recorded during the month of July for a given location.
-
C.
hasAverageSpringTemperature
Indicates that an entity is associated with a specific average temperature value measured over the spring season.
-
D.
averageHighTemperatureInJanuary
Indicates the typical or mean value of the highest daily temperatures recorded during the month of January for a given location.
-
E.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef691cc8819091729eaac52c9457 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2ede3187c8190a7ced078f0ec3476 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.