Triple
T10079621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middletown, Connecticut |
E213864
|
entity |
| Predicate | mergedTownAndCityGovernments |
P80558
|
FINISHED |
| Object | 1923 |
—
|
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: 1923 | Statement: [Middletown, Connecticut, mergedTownAndCityGovernments, 1923]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mergedTownAndCityGovernments Context triple: [Middletown, Connecticut, mergedTownAndCityGovernments, 1923]
-
A.
hasMunicipalConsolidationWith
chosen
Indicates that two or more municipalities have been officially merged or unified into a single administrative entity or structure.
-
B.
formerMunicipalityOf
Indicates that an entity was previously an independent municipality that has since been merged into or replaced by the referenced municipality.
-
C.
hasCityGovernmentType
Indicates the specific form or structure of municipal governance that administers a city.
-
D.
municipalityReform
Indicates a formal reorganization or restructuring of a municipality’s administrative boundaries, governance, or status.
-
E.
restructuredGovernmentOf
Indicates that one entity has reorganized or significantly altered the governmental structure or system of 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd031ce748190bb71189afd331979 |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9 p.m.