Triple
T28599144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juan Manuel de Rosas–Villa Urquiza station |
E723857
|
entity |
| Predicate | terminalOfLine |
P46766
|
FINISHED |
| Object | Line B (Buenos Aires Underground) |
—
|
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 B (Buenos Aires Underground) | Statement: [Juan Manuel de Rosas–Villa Urquiza station, terminalOfLine, Line B (Buenos Aires Underground)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terminalOfLine Context triple: [Juan Manuel de Rosas–Villa Urquiza station, terminalOfLine, Line B (Buenos Aires Underground)]
-
A.
lineTerminusFor
chosen
Indicates that one entity serves as an endpoint or terminus of a particular line or linear feature represented by another entity.
-
B.
terminalLocation
Indicates the specific terminal or endpoint location associated with an entity or process.
-
C.
terminalName
Indicates the name or label assigned to a specific terminal or endpoint within a system or network.
-
D.
lineTerminusDirection
Indicates the directional orientation or bearing at which a line segment or route terminates at its endpoint.
-
E.
lineTerminal2
Indicates that the referenced entity serves as the second terminal (endpoint) of a line.
- 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_69f01d80b1908190980594837604b8c7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 28, 2026, 4:23 a.m.