Triple
T18981707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Jersey City |
E464442
|
entity |
| Predicate | notAn |
P28211
|
FINISHED |
| Object | incorporated municipality |
—
|
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: incorporated municipality | Statement: [South Jersey City, notAn, incorporated municipality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notAn Context triple: [South Jersey City, notAn, incorporated municipality]
-
A.
notAbout
Indicates that a given entity, statement, or resource does not concern, reference, or pertain to another specified entity or topic.
-
B.
notStatus
Indicates that an entity does not have, is not in, or does not match a specified status or state.
-
C.
notTypically
Indicates that the referenced situation, behavior, or relationship does not usually or normally occur under standard or expected conditions.
-
D.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
-
E.
nonExample
chosen
Indicates that something is explicitly identified as not being an example or instance of a given concept, category, or pattern.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d65d27548190b86d4c5f5b51d809 |
completed | April 20, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:01 p.m.