Triple
T72117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greek American |
E1443
|
entity |
| Predicate | typicalSettlementPattern |
P1830
|
FINISHED |
| Object | urban areas in the United States |
—
|
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: urban areas in the United States | Statement: [Greek American, typicalSettlementPattern, urban areas in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSettlementPattern Context triple: [Greek American, typicalSettlementPattern, urban areas in the United States]
-
A.
hadPrimarySettlementPattern
chosen
Indicates that an entity exhibited or was characterized by a particular dominant form or arrangement of human settlement.
-
B.
settlementType
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
-
C.
servesSettlement
Indicates that one entity provides services or support to a particular settlement or community.
-
D.
inspiredSettlement
Indicates that one entity’s ideas, actions, or example motivated or influenced the creation, development, or characteristics of a particular settlement.
-
E.
originalSettlement
Indicates that one entity is the initial or first-established settlement location associated with another entity.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.