Triple
T27741829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey politics |
E701873
|
entity |
| Predicate | municipalityCount |
P30910
|
FINISHED |
| Object | over 560 |
—
|
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: over 560 | Statement: [New Jersey politics, municipalityCount, over 560]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: municipalityCount Context triple: [New Jersey politics, municipalityCount, over 560]
-
A.
hasNumberOfMunicipalities
chosen
Indicates the relationship that specifies how many municipalities are associated with or contained within a given administrative or geographic entity.
-
B.
municipalityPopulation
Indicates the total number of inhabitants living within a given municipality.
-
C.
numberOfRegionalCouncils
Indicates the total count of regional councils associated with a given entity.
-
D.
numberOfAutonomousCommunities
Indicates the quantity of autonomous communities associated with or contained within a given entity.
-
E.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 27, 2026, 4:11 p.m.