Triple
T17450566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Lewis |
E424900
|
entity |
| Predicate | fillingTimeScale |
P9981
|
FINISHED |
| Object | days to weeks |
—
|
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: days to weeks | Statement: [Lake Lewis, fillingTimeScale, days to weeks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fillingTimeScale Context triple: [Lake Lewis, fillingTimeScale, days to weeks]
-
A.
focusesOnTimeScale
Indicates that something is concerned with, analyzes, or is defined in terms of a particular time scale or temporal granularity.
-
B.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
-
C.
timeScaleCategory
Indicates the classification of an event or process based on the temporal scale or duration over which it occurs.
-
D.
supportsTimescale
Indicates that one entity is capable of operating with, accommodating, or being compatible with a specified timescale or range of temporal resolutions.
-
E.
timescale
chosen
Indicates the temporal scale or duration over which a process, relationship, or effect occurs or is evaluated.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4513d00f48190802a3bdc8c8f4db5 |
completed | April 19, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f0e3fc819094e466b74622c956 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:47 a.m.