Triple
T29610294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macmerry |
E754696
|
entity |
| Predicate | hasLandUseHistorically |
P44099
|
FINISHED |
| Object | arable farming |
—
|
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: arable farming | Statement: [Macmerry, hasLandUseHistorically, arable farming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandUseHistorically Context triple: [Macmerry, hasLandUseHistorically, arable farming]
-
A.
hasHistoricalLandCover
Indicates that an entity is associated with information about the land cover that existed in a specified area during a past time period.
-
B.
historicalUseOfArea
Indicates how an area was used or what activities occurred there during a past period.
-
C.
formerLandUse
chosen
Indicates the type of land use that characterized a location prior to its current or present use.
-
D.
historicalHabitat
Indicates that an entity previously lived, occurred, or was distributed within a particular habitat or environment in the past.
-
E.
hasHistoricLandGrants
Indicates that an entity has been granted land through one or more historically significant official land grants.
- 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_69f0ef85f62081909842b59fdf8717e1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
Created at: April 28, 2026, 6:28 p.m.