Triple
T18840375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tonlé Sap Lake |
E460776
|
entity |
| Predicate | averageDepthWetSeason |
P1176
|
FINISHED |
| Object | around 8–9 meters |
—
|
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: around 8–9 meters | Statement: [Tonlé Sap Lake, averageDepthWetSeason, around 8–9 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageDepthWetSeason Context triple: [Tonlé Sap Lake, averageDepthWetSeason, around 8–9 meters]
-
A.
maximumWaterDepth
Indicates the greatest depth of water present or allowed in a given context, such as a location, container, or body of water.
-
B.
riverbedDepth
Indicates the depth or vertical distance from the water surface to the bottom of a river at a given location or time.
-
C.
wetSeasonAccessibility
Indicates how easily or reliably something can be reached, used, or traversed during the wet or rainy season.
-
D.
lakeMaximumDepth
Indicates the greatest recorded vertical distance from the lake’s surface to its deepest point.
-
E.
hasAverageDepth
chosen
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5b8e8f57081909edbbcaf56189816 |
completed | April 20, 2026, 5:26 a.m. |
| PD | Predicate disambiguation | batch_69e48d1e7dac81909ea1e758c87773c5 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:56 a.m.