Triple
T3657294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Amada site |
E77561
|
entity |
| Predicate | originalSiteSubmergedBy |
P42186
|
FINISHED |
| Object | waters of Lake Nasser |
—
|
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: waters of Lake Nasser | Statement: [New Amada site, originalSiteSubmergedBy, waters of Lake Nasser]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalSiteSubmergedBy Context triple: [New Amada site, originalSiteSubmergedBy, waters of Lake Nasser]
-
A.
submergedBy
chosen
Indicates that one entity is covered or overwhelmed by liquid, typically water, to the point of being beneath its surface due to the action or presence of another entity.
-
B.
submerged
Indicates that one entity is located beneath the surface of a liquid or other surrounding medium, typically fully covered by it.
-
C.
hasSubmergedArchaeologicalRemains
Indicates that an entity contains or is associated with archaeological remains that are located underwater or below a water surface.
-
D.
sunkBy
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
-
E.
sunk
Indicates that one entity caused another entity to go below the surface of a liquid, typically water, so that it is submerged or destroyed.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d36c1c8190920397a75de4c47d |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb84650148190bf79231105e58d7f |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.