Triple
T28088603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estación Carlos Pellegrini |
E709893
|
entity |
| Predicate | connectsLineViaTransfer |
P174228
|
FINISHED |
| Object | Line C |
—
|
NE NERFINISHED |
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: Line C | Statement: [Estación Carlos Pellegrini, connectsLineViaTransfer, Line C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsLineViaTransfer Context triple: [Estación Carlos Pellegrini, connectsLineViaTransfer, Line C]
-
A.
connectedLine
Indicates that two entities are joined by a continuous line or linear connection.
-
B.
transferAvailableToLine
chosen
Indicates that a transfer option is available from one service or route to a specific transit line.
-
C.
networkLine
Indicates that there is a connection or linkage between entities within a network structure or system.
-
D.
allowsTransferBetweenLinesAt
Indicates that an entity permits passengers to transfer between different transit lines at a specific location or point.
-
E.
connectsCitiesViaLine
Indicates a relationship where a transportation line directly links two or more cities.
- 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_69ef9b7037f0819095bb90eaccbcaf32 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: April 27, 2026, 8:56 p.m.