Triple
T4129242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of the State of New Jersey |
E84999
|
entity |
| Predicate | legislativeDistricts |
P43366
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [Government of the State of New Jersey, legislativeDistricts, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legislativeDistricts Context triple: [Government of the State of New Jersey, legislativeDistricts, 40]
-
A.
congressionalDistrict
Indicates that one entity is a congressional district that politically represents or geographically contains the other entity.
-
B.
stateHouseDistrict
Indicates the specific state-level legislative house district in which an entity is located or to which it is assigned.
-
C.
electoralAreaOf
Indicates that a given electoral area (such as a district or ward) is the designated electoral division associated with a particular jurisdiction or entity.
-
D.
servedDistrict
Indicates that an entity has provided official service or representation to a particular district.
-
E.
hasElectoralDistricts
chosen
Indicates that a political or administrative unit is divided into one or more electoral districts used for representation or voting.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:42 p.m.