Triple
T13408111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Settlement, Greenland |
E320013
|
entity |
| Predicate | estimatedFarmCount |
P109793
|
FINISHED |
| Object | about 190 farms |
—
|
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: about 190 farms | Statement: [Eastern Settlement, Greenland, estimatedFarmCount, about 190 farms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedFarmCount Context triple: [Eastern Settlement, Greenland, estimatedFarmCount, about 190 farms]
-
A.
tenantFarmersCount
Indicates the number of tenant farmers associated with a particular landholding, property, or area.
-
B.
hasNotableFarm
Indicates that an entity possesses or is associated with a farm that is considered notable or significant in some recognized way.
-
C.
isPredominantlyRural
Indicates that a place or region is characterized mainly by rural features, such as low population density and extensive non-urban land use.
-
D.
hasNumberOfAcres
Indicates the specific quantity of land area, measured in acres, that is associated with an entity.
-
E.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4d2c5481908facfaaa1501e344 |
completed | April 12, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:35 p.m.