Triple
T4014377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuuk Lagoon |
E90719
|
entity |
| Predicate | numberOfShipwrecks |
P53939
|
FINISHED |
| Object | over 40 shipwrecks |
—
|
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: over 40 shipwrecks | Statement: [Chuuk Lagoon, numberOfShipwrecks, over 40 shipwrecks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfShipwrecks Context triple: [Chuuk Lagoon, numberOfShipwrecks, over 40 shipwrecks]
-
A.
hasShipwrecks
Indicates that one entity contains, includes, or is associated with shipwrecks located within it or under its control.
-
B.
shipwreckEvent
Indicates an event in which a ship is destroyed, stranded, or severely damaged, typically resulting in loss or abandonment at sea or near a shoreline.
-
C.
shipwreckUse
Indicates that an entity makes use of, interacts with, or derives benefit from a shipwreck.
-
D.
shipsSunkOrTotalLoss
Indicates that the referenced ships were sunk or otherwise rendered a total loss (permanently unusable).
-
E.
causeOfShipwreck
Indicates the factor, event, or condition that directly led to a shipwreck occurring.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaec08dc8190a341809059554f84 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fa6fec81909b1190ecbba61410 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefaea76c48190add2e7cee180e8b1 |
completed | March 9, 2026, 4:52 p.m. |
Created at: March 9, 2026, 3:35 p.m.