Triple
T24600259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1870 United States census |
E608802
|
entity |
| Predicate | numberOfStatesEnumerated |
P14077
|
FINISHED |
| Object | 37 |
—
|
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: 37 | Statement: [1870 United States census, numberOfStatesEnumerated, 37]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStatesEnumerated Context triple: [1870 United States census, numberOfStatesEnumerated, 37]
-
A.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
B.
requiredNumberOfStates
Indicates the specific number of distinct states that something must have or support in order to meet a given requirement or condition.
-
C.
numberOfProvinces
Indicates the total count of provinces associated with a given entity or within a specified region or country.
-
D.
numberOfStatesRepresented
chosen
Indicates how many distinct states are represented or covered in a given context or entity.
-
E.
hasNumberOfStatesAndDistricts
Indicates a relationship where an entity is associated with a specific count of its constituent states and districts.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.