Triple
T22730044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Ward (Newark) |
E562109
|
entity |
| Predicate | numberOfMunicipalWardsInNewark |
P63824
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [West Ward (Newark), numberOfMunicipalWardsInNewark, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMunicipalWardsInNewark Context triple: [West Ward (Newark), numberOfMunicipalWardsInNewark, 5]
-
A.
numberOfWards
chosen
Indicates the quantitative relationship specifying how many wards are associated with a given entity.
-
B.
hasMunicipalWards
Indicates that a municipality is divided into and associated with one or more municipal wards as its internal administrative units.
-
C.
numberOfBoroughs
Indicates the total count of boroughs associated with a given entity.
-
D.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
E.
numberOfSpecialWards
Indicates the count of wards that are designated as special within a given context or entity.
- 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1792cb9cc8190a7c45032427bca1a |
completed | April 29, 2026, 3:21 a.m. |
| PD | Predicate disambiguation | batch_69eed2a971c0819088af574e40c9343f |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:21 p.m.