Triple
T1226518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid Metro |
E26338
|
entity |
| Predicate | hasUndergroundSections |
P15152
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Madrid Metro, hasUndergroundSections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUndergroundSections Context triple: [Madrid Metro, hasUndergroundSections, yes]
-
A.
hasUndergroundSection
chosen
Indicates that an entity includes a portion or segment that is located below ground level.
-
B.
hasUndergroundSlide
Indicates that one entity features or includes an underground slide connecting it to another location or structure.
-
C.
hasUnderpass
Indicates that one location or structure includes or is connected by an underpass beneath another feature or pathway.
-
D.
hasShuttleLine
Indicates that there is a shuttle service or route operating between the related entities.
-
E.
subwayLine
Indicates that there is a subway line connection or service relationship between the referenced entities.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be39908481908cca21aaf0828415 |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb65d61c8190bf0424ea0019a98b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.