Triple
T28645635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scharnebeck twin ship lift |
E725046
|
entity |
| Predicate | hasTroughType |
P194354
|
FINISHED |
| Object | counterweighted water-filled trough |
—
|
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: counterweighted water-filled trough | Statement: [Scharnebeck twin ship lift, hasTroughType, counterweighted water-filled trough]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTroughType Context triple: [Scharnebeck twin ship lift, hasTroughType, counterweighted water-filled trough]
-
A.
hasTrough
Indicates that one entity possesses, includes, or is characterized by a trough, such as a long, narrow, typically low or recessed feature or container.
-
B.
hasNumberOfTroughs
Indicates the relationship that specifies how many troughs (local minima) are present in a given pattern, signal, or function.
-
C.
hasTrailType
Indicates that an entity (such as a trail or route) is associated with a specific type or category of trail.
-
D.
troughWidth
Indicates the measured width of a trough in a given context or system.
-
E.
troughLength
Indicates the measured longitudinal extent or distance from one end of a trough to the other.
- 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_69f01d8423888190bd2f4e52605bf261 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fd6dbd1b648190b1a0b391c03aebc5 |
completed | May 8, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69fd6a9020548190bbfa845360ac85fb |
completed | May 8, 2026, 4:46 a.m. |
| PDg | Predicate description generation | batch_69fd6dbc3ac0819093fbcfe95f12b93d |
completed | May 8, 2026, 4:59 a.m. |
Created at: April 28, 2026, 4:47 a.m.