Triple
T24621622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trängslet Dam |
E609426
|
entity |
| Predicate | rankInSwedenByHeight |
P156776
|
FINISHED |
| Object | one of the highest dams in Sweden |
—
|
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: one of the highest dams in Sweden | Statement: [Trängslet Dam, rankInSwedenByHeight, one of the highest dams in Sweden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInSwedenByHeight Context triple: [Trängslet Dam, rankInSwedenByHeight, one of the highest dams in Sweden]
-
A.
countryRankByHeight
Indicates the relative position of a country when countries are ordered by the height of something (e.g., average elevation, tallest point, or average citizen height).
-
B.
rankingInUnitedKingdomByHeight
Indicates the position of an entity in an ordered list based on its height within the United Kingdom.
-
C.
rankingByHeightInIsrael
Indicates an ordering of entities based on their relative heights within the context of Israel.
-
D.
rankByHeightWorld
Indicates an ordering of entities based on their relative height compared to all others in the world.
-
E.
rankByHeightInAustria
Indicates that entities are ordered or compared according to their height specifically within the context of Austria.
- 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_69e2c4d1d3708190a0f2dc6a3a8523bb |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:32 a.m.