Triple
T25662966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sector 4 City Hall |
E643434
|
entity |
| Predicate | sectorNumber |
P115725
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Sector 4 City Hall, sectorNumber, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorNumber Context triple: [Sector 4 City Hall, sectorNumber, 4]
-
A.
sectorCountApprox
Indicates that the number of sectors involved is an approximate or estimated count rather than an exact value.
-
B.
sectorBase
Indicates that one entity serves as the primary base or foundational location for operations within a particular sector of another entity.
-
C.
sectorCountReferenced
chosen
Indicates that one entity specifies or refers to the number of sectors associated with another entity.
-
D.
positionInSector
Indicates the specific location or placement of an entity within a defined sector or sub-area.
-
E.
boroughNumber
Indicates the numerical identifier assigned to a specific borough within a larger administrative or municipal division.
- 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_69e77e7e45648190a068ed3faa8016ea |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 21, 2026, 6:57 p.m.