Triple
T28088704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estación 9 de Julio |
E709895
|
entity |
| Predicate | hasUndergroundCorridorsTo |
P41500
|
FINISHED |
| Object | Estación Carlos Pellegrini |
—
|
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: Estación Carlos Pellegrini | Statement: [Estación 9 de Julio, hasUndergroundCorridorsTo, Estación Carlos Pellegrini]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUndergroundCorridorsTo Context triple: [Estación 9 de Julio, hasUndergroundCorridorsTo, Estación Carlos Pellegrini]
-
A.
hasUndergroundLevel
Indicates that one entity possesses or includes a level, floor, or section that is located below ground level.
-
B.
hasUndergroundSection
Indicates that an entity includes a portion or segment that is located below ground level.
-
C.
hasUndergroundVestibule
Indicates that one entity possesses or includes an underground vestibule space connected to it.
-
D.
hasUndergroundFacilities
Indicates that one entity possesses or contains facilities or infrastructure located below ground level in relation to another entity.
-
E.
hasUndergroundConnections
chosen
Indicates that one entity is linked to another through subterranean or hidden passageways, networks, or channels.
- 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_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 27, 2026, 8:57 p.m.