Triple
T12461379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Nemi |
E297800
|
entity |
| Predicate | shipwrecksRecoveredIn |
P105137
|
FINISHED |
| Object | 1930s |
—
|
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: 1930s | Statement: [Lake Nemi, shipwrecksRecoveredIn, 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipwrecksRecoveredIn Context triple: [Lake Nemi, shipwrecksRecoveredIn, 1930s]
-
A.
hasShipwrecks
Indicates that one entity contains, includes, or is associated with shipwrecks located within it or under its control.
-
B.
numberOfShipwrecks
Indicates the quantity of shipwrecks associated with a given entity or context.
-
C.
wreckDiscovery
Indicates that an entity discovers, finds, or identifies a wreck (such as a ruined or destroyed object, vehicle, or structure).
-
D.
shipsSunkOrTotalLoss
Indicates that the referenced ships were sunk or otherwise rendered a total loss (permanently unusable).
-
E.
shipwreckUse
Indicates that an entity makes use of, interacts with, or derives benefit from a shipwreck.
- F. None of above. chosen
Provenance (4 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94e5f8d04819086d1ad4d62364005 |
completed | April 10, 2026, 7:24 p.m. |
Created at: April 8, 2026, 9:56 p.m.