Triple
T35827273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germanna Ford |
E1035681
|
entity |
| Predicate | nearHistoricSettlement |
P54388
|
FINISHED |
| Object | Germanna |
—
|
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: Germanna | Statement: [Germanna Ford, nearHistoricSettlement, Germanna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearHistoricSettlement Context triple: [Germanna Ford, nearHistoricSettlement, Germanna]
-
A.
traditionalSettlement
Indicates that an entity is a settlement characterized by long-established, customary, or historically rooted patterns of habitation and land use.
-
B.
locatedInOrNearModernSettlement
chosen
Indicates that something is situated within or in close proximity to a present-day town, city, or other populated settlement.
-
C.
containsHistoricTown
Indicates that one entity geographically includes or encompasses a town that has recognized historical significance.
-
D.
traditionalSettlementArea
Indicates that an area is recognized as a traditional settlement zone associated with a particular group or community.
-
E.
historicalSettlementType
Indicates the type or category of settlement an entity was historically classified as (e.g., village, town, city) during a past period.
- 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_69f76e185ffc8190880b3cdf51decd38 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.