Triple
T27741828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey politics |
E701873
|
entity |
| Predicate | countyCount |
P27148
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [New Jersey politics, countyCount, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countyCount Context triple: [New Jersey politics, countyCount, 21]
-
A.
hasNumberOfCounties
chosen
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
B.
countyNumberInState
Indicates the ordinal position or identifying number assigned to a county within its state.
-
C.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
D.
numberPerCounty
Indicates the quantity or count of something associated with each individual county.
-
E.
countyNumberInStateFormation
Indicates the ordinal position a county held among all counties created within a particular state at the time of that state's formation.
- 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_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: April 27, 2026, 4:11 p.m.