Triple
T421110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bronx |
E8102
|
entity |
| Predicate | onlyNYCBoroughOnMainland |
P14726
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Bronx, onlyNYCBoroughOnMainland, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onlyNYCBoroughOnMainland Context triple: [The Bronx, onlyNYCBoroughOnMainland, true]
-
A.
numberOfBoroughs
Indicates the total count of boroughs associated with a given entity.
-
B.
incorporatedAsBorough
Indicates that an entity was formally established and granted legal status as a borough.
-
C.
largestBoroughByAreaOf
Indicates that one entity is the borough with the greatest land area within the jurisdiction or region specified by the other entity.
-
D.
largestBoroughByPopulationOf
Indicates that one entity is the borough with the highest population within the other entity (typically a city or region).
-
E.
hasBorough
Indicates that one entity is located within, belongs to, or is administratively part of a specific borough.
- F. None of above. chosen
Provenance (4 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebf65cc81908196fee4f09d5889 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd3b948819097d96c73d0a0f699 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb8545c8190a2b8517e7ed5b92e |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.