Triple
T792809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marthasville |
E16951
|
entity |
| Predicate | formerSettlementType |
P16344
|
FINISHED |
| Object | railroad town |
—
|
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: railroad town | Statement: [Marthasville, formerSettlementType, railroad town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerSettlementType Context triple: [Marthasville, formerSettlementType, railroad town]
-
A.
originalSettlement
Indicates that one entity is the initial or first-established settlement location associated with another entity.
-
B.
formerType
chosen
Indicates that one entity previously had a certain type, role, or classification but no longer does.
-
C.
settlementType
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
-
D.
traditionalSettlement
Indicates that an entity is a settlement characterized by long-established, customary, or historically rooted patterns of habitation and land use.
-
E.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a79a3bbc81908d818c50a366b0f8 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a510f61881909175d6d8719246cd |
completed | March 1, 2026, 8:44 p.m. |
Created at: March 1, 2026, 7:38 p.m.