Triple
T8566733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabey |
E202820
|
entity |
| Predicate | cityExplored |
P16949
|
FINISHED |
| Object | New York City boroughs |
—
|
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: New York City boroughs | Statement: [Gabey, cityExplored, New York City boroughs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityExplored Context triple: [Gabey, cityExplored, New York City boroughs]
-
A.
cityPanorama
Indicates a wide, comprehensive visual view or representation of a cityscape, typically encompassing many of its features in a single scene.
-
B.
placesWithin
Indicates that one place or area is located entirely inside the boundaries of another place or area.
-
C.
visitedLocation
chosen
Indicates that an entity has gone to or spent time at a particular location.
-
D.
journeyDestination
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
E.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9d467c08190b2014d71ebbf8bbc |
completed | March 31, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:20 p.m.