Triple
T30098247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 19th-century Connecticut |
E764923
|
entity |
| Predicate | hadDemographicChange |
P151124
|
FINISHED |
| Object | rising urban population |
—
|
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: rising urban population | Statement: [19th-century Connecticut, hadDemographicChange, rising urban population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadDemographicChange Context triple: [19th-century Connecticut, hadDemographicChange, rising urban population]
-
A.
demographicImpact
Indicates how an action, event, or condition affects the size, structure, or composition of a population.
-
B.
hasDemographic
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
C.
hadPopulationFrom
Indicates that an entity had a specified population value during a particular time period starting from a given date.
-
D.
hasDemographicProcess
chosen
Indicates a relationship where a population or group undergoes a specific demographic process, such as birth, death, migration, or aging.
-
E.
changedUnder
Indicates that one entity has undergone alteration, modification, or transformation as a result of the influence, action, or conditions imposed by 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_69f22474e4288190b5f895fe3974aa92 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67d92dbdc8190ae3e8f67b979cb5c |
completed | May 2, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:07 p.m.