Triple
T15757482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manhattan and the Bronx |
E382003
|
entity |
| Predicate | areLinkedFor |
P42454
|
FINISHED |
| Object | commuting |
—
|
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: commuting | Statement: [Manhattan and the Bronx, areLinkedFor, commuting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areLinkedFor Context triple: [Manhattan and the Bronx, areLinkedFor, commuting]
-
A.
canBeLinkedTo
Indicates that one entity has the potential or capability to be connected or associated with another entity.
-
B.
commonlyLinkedTo
Indicates that one entity is frequently or typically associated, connected, or co-occurring with another entity.
-
C.
linkedByStructure
Indicates that two entities are connected or associated through a shared structural element, configuration, or framework.
-
D.
linkedToDate
Indicates that an entity is associated or connected to a specific date or point in time.
-
E.
linkedNetwork
chosen
Indicates that two entities are connected through a shared or associated network relationship.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b1ff4881909d5240d1d30f5c8b |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.