Triple
T31338779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Layde |
E799246
|
entity |
| Predicate | containsTownland |
P200082
|
FINISHED |
| Object | Layde townland |
—
|
NE NERFINISHED |
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: Layde townland | Statement: [Layde, containsTownland, Layde townland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsTownland Context triple: [Layde, containsTownland, Layde townland]
-
A.
hasTownlandStatus
Indicates that an entity holds the legal or administrative status of being a townland.
-
B.
hasRuralParish
Indicates that an entity possesses or is associated with a rural parish as an administrative or ecclesiastical subdivision.
-
C.
regionContainsTowns
Indicates that a geographic region includes or encompasses one or more towns within its boundaries.
-
D.
historicalTownshipOf
Indicates that one entity was formerly a township encompassing or governing the other entity during a past historical period.
-
E.
hasCivilParishComponent
Indicates that an entity includes or is composed of the specified civil parish as one of its administrative components.
- 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_69f224e3f6ac8190a13488516abca7c9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff70ecc1a481909571b18d56d982b8 |
completed | May 9, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69ff70322a3c8190837840ea42cd3093 |
completed | May 9, 2026, 5:34 p.m. |
| PDg | Predicate description generation | batch_69ff70ebec7481908d8a4124c8d531df |
completed | May 9, 2026, 5:37 p.m. |
Created at: April 29, 2026, 9:16 p.m.