Triple
T9212369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Saint-Pierre |
E221153
|
entity |
| Predicate | numberOfIslandsApproximate |
P83748
|
FINISHED |
| Object | about 100 |
—
|
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: about 100 | Statement: [Lake Saint-Pierre, numberOfIslandsApproximate, about 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIslandsApproximate Context triple: [Lake Saint-Pierre, numberOfIslandsApproximate, about 100]
-
A.
approximateNumberOfIslands
chosen
Indicates an estimated or rough count of how many islands are present or associated with a given context.
-
B.
numberOfIslands
Indicates the total count of distinct, separate landmasses (islands) present within a given area or context.
-
C.
hasApproximateIslandsCount
Indicates that an entity is associated with an estimated or non-exact number of islands.
-
D.
numberOfArtificialIslands
Indicates the quantitative count of artificial islands associated with or contained within a given entity.
-
E.
connectedIsland
Indicates that two islands are linked by a direct or indirect path, such that travel or communication between them is possible within the same connected group.
- 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda05406081909893bec3a092d3ce |
completed | April 1, 2026, 8:40 a.m. |
| PD | Predicate disambiguation | batch_69cc660ce23c81909c7bbe10f4a05f36 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:27 p.m.