Triple
T34439780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SQ22 |
E884064
|
entity |
| Predicate | operatesNonstopBetween |
P202475
|
FINISHED |
| Object | Singapore and New York |
—
|
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: Singapore and New York | Statement: [SQ22, operatesNonstopBetween, Singapore and New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesNonstopBetween Context triple: [SQ22, operatesNonstopBetween, Singapore and New York]
-
A.
operatesBetweenCity
chosen
Indicates a transportation or service route that runs between two cities.
-
B.
operatesCommuterServiceBetween
Indicates that an entity runs a commuter transportation service connecting two specified locations.
-
C.
operatedBetweenStations
Indicates that an operation, such as a service or route, took place connecting or running between two specified stations.
-
D.
operatesBetween
Indicates a relationship where an action, process, or influence functions or takes effect in the space, interval, or context separating two entities.
-
E.
servesRailTrafficBetween
Indicates that something (typically a rail line, service, or facility) provides rail transportation connecting two or more locations.
- 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_69f349c548d88190978e2a82502c03d0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a00b34364448190b8c9948d5a24d845 |
completed | May 10, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_6a00b2e4f13c819081bac7d763c414ad |
completed | May 10, 2026, 4:31 p.m. |
Created at: May 1, 2026, 2 a.m.