Triple
T22900603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin Township |
E568302
|
entity |
| Predicate | FIPSCodeJurisdiction |
P227
|
FINISHED |
| Object | 34 (New Jersey) |
—
|
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: 34 (New Jersey) | Statement: [Berlin Township, FIPSCodeJurisdiction, 34 (New Jersey)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FIPSCodeJurisdiction Context triple: [Berlin Township, FIPSCodeJurisdiction, 34 (New Jersey)]
-
A.
FIPSCode
chosen
Indicates the standardized Federal Information Processing Standards (FIPS) code assigned to identify a specific geographic or administrative entity.
-
B.
USStateFIPSLocation
Indicates a locational relationship where a place or entity is situated within, or associated with, a U.S. state identified by its FIPS (Federal Information Processing Standards) code.
-
C.
hasISO3166-2CodePrefix
Indicates that one entity’s ISO 3166-2 code begins with, or is prefixed by, the code of another entity.
-
D.
includesFederalDistrict
Indicates that one administrative or geographic entity contains or encompasses a federal district within its boundaries.
-
E.
federalDistrictType
Indicates the specific category or classification of a federal district within a governmental or administrative system.
- 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1801626488190b7e8ce3301667987 |
completed | April 29, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69ef3b6b2e2481908258156937b5a745 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:41 p.m.