Triple
T168855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MetroCard |
E3073
|
entity |
| Predicate | canBeUsedOn |
P2367
|
FINISHED |
| Object | local buses in New York City |
—
|
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: local buses in New York City | Statement: [MetroCard, canBeUsedOn, local buses in New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeUsedOn Context triple: [MetroCard, canBeUsedOn, local buses in New York City]
-
A.
usedOn
chosen
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
B.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
-
C.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
D.
canAlsoBe
Indicates that something has an additional possible state, role, or classification beyond its primary one.
-
E.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258b6f4f88190b1264bbbeb19a29e |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25665f5b8819096ca3e084faf976e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.