Triple
T13531947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downtown (NYC Subway Direction) |
E323153
|
entity |
| Predicate | outerBoroughMeaning |
P110725
|
FINISHED |
| Object | toward Manhattan |
—
|
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: toward Manhattan | Statement: [Downtown (NYC Subway Direction), outerBoroughMeaning, toward Manhattan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: outerBoroughMeaning Context triple: [Downtown (NYC Subway Direction), outerBoroughMeaning, toward Manhattan]
-
A.
otherBoroughs
Indicates that two locations are in different boroughs within the same city or metropolitan area.
-
B.
primaryBorough
Indicates that one borough is the main or most significant borough associated with a given entity.
-
C.
hasBoroughEndpoint
Indicates that something has an endpoint located within a specific borough.
-
D.
primaryBoroughFocus
Indicates that something has its main or most significant emphasis, activity, or attention centered on a particular borough.
-
E.
realWorldBorough
Indicates that an entity is located in, associated with, or belongs to a specific real-world 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafbb34548190a6b44faa48125cd4 |
completed | April 12, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:44 p.m.