Triple
T31901381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oxenhope railway station |
E814430
|
entity |
| Predicate | hasWaterColumn |
P181170
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Oxenhope railway station, hasWaterColumn, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterColumn Context triple: [Oxenhope railway station, hasWaterColumn, true]
-
A.
hasWaterChannel
Indicates that one entity possesses or contains a channel or conduit through which water flows or is transported.
-
B.
hasWaterFunction
Indicates that an entity performs, provides, or is associated with a specific function or role related to water.
-
C.
hasBottomWater
Indicates that an entity contains or is associated with water specifically located at its bottom or lowest part.
-
D.
waterColumnProperty
Indicates a relationship where a specified property characterizes or describes some aspect of a water column (e.g., its physical, chemical, or biological state).
-
E.
hasWaterLevelCharacteristic
Indicates that an entity is associated with a specific property, feature, or behavior related to its water level.
- 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_69f348f04d7881909537fc9e7cbc670e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
| PDg | Predicate description generation | batch_69f762651e088190baa21f25378a6065 |
completed | May 3, 2026, 2:57 p.m. |
Created at: April 30, 2026, 11:59 p.m.