Triple
T24433465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Torpenhow |
E616059
|
entity |
| Predicate | hasPlaceNameElement |
P96333
|
FINISHED |
| Object | Old English "how" meaning hill |
—
|
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: Old English "how" meaning hill | Statement: [Torpenhow, hasPlaceNameElement, Old English "how" meaning hill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlaceNameElement Context triple: [Torpenhow, hasPlaceNameElement, Old English "how" meaning hill]
-
A.
hasPlaceNamesIn
Indicates that something contains, references, or is associated with one or more place names within it.
-
B.
hasStreetNameElement
Indicates that an address or location includes a specific street name component as part of its full designation.
-
C.
hasStationNameElement
Indicates that a station is associated with a specific name component or element used as part of its full station name.
-
D.
toponymyContainsElement
chosen
Indicates that a toponym (place name) includes a specific linguistic or semantic element as part of its composition.
-
E.
hasPlaceNamesakeIn
Indicates that something is named after a particular place or location.
- 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_69e2d7ec44b081909ccaf1f3bbec0641 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2978469a081909f17b6955809bbef |
completed | April 29, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:16 a.m.