Triple
T2350259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elmont, New York |
E47430
|
entity |
| Predicate | historicalLandUse |
P2417
|
FINISHED |
| Object | farmland |
—
|
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: farmland | Statement: [Elmont, New York, historicalLandUse, farmland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalLandUse Context triple: [Elmont, New York, historicalLandUse, farmland]
-
A.
historicUsePersistsIn
Indicates that a practice, feature, or condition originating in the past continues to exist or be applied in the present.
-
B.
historicalPeriodOfUse
Indicates the time period during which something was in active use or commonly utilized.
-
C.
historicallyUsedFor
chosen
Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
-
D.
historicalLanguageOfEnvironment
Indicates that a language was historically used or prevalent in a given environment or setting, even if it is not the current primary language there.
-
E.
historicalStatusOf
Indicates the historical condition, role, or classification that an entity held during a specific past period or context.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:54 p.m.