Triple
T35935824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Settlement, Greenland |
E1039301
|
entity |
| Predicate | numberOfFarms |
P109793
|
FINISHED |
| Object | approximately 90 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: approximately 90 farms | Statement: [Western Settlement, Greenland, numberOfFarms, approximately 90 farms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFarms Context triple: [Western Settlement, Greenland, numberOfFarms, approximately 90 farms]
-
A.
estimatedFarmCount
chosen
Indicates the estimated number of farms associated with or present in a given context or entity.
-
B.
tenantFarmersCount
Indicates the number of tenant farmers associated with a particular landholding, property, or area.
-
C.
servesAsFarmSystemFor
Indicates that one entity functions as a developmental or feeder system that supplies trained or prepared resources (such as players, talent, or products) to another entity.
-
D.
hasFarm
Indicates that one entity owns, operates, or is responsible for a farm associated with another entity.
-
E.
hasNotableFarm
Indicates that an entity possesses or is associated with a farm that is considered notable or significant in some recognized way.
- 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_69f76e24bbd0819096b837d35371639a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.