Triple
T5575866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 4 (Madrid Metro) |
E146316
|
entity |
| Predicate | connectsCommercialAreas |
P64531
|
FINISHED |
| Object | Madrid commercial districts |
—
|
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: Madrid commercial districts | Statement: [Line 4 (Madrid Metro), connectsCommercialAreas, Madrid commercial districts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCommercialAreas Context triple: [Line 4 (Madrid Metro), connectsCommercialAreas, Madrid commercial districts]
-
A.
connectsArea
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
B.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
C.
commercialArea
Indicates that the location or region is designated primarily for commercial activities such as businesses, shops, or services.
-
D.
connectsCityTo
Indicates a relationship in which a route, infrastructure, or link joins one city to another, enabling connection or interaction between them.
-
E.
connectsCityIndirectly
Indicates that one location is linked to a city through one or more intermediate locations or routes, rather than by a direct connection.
- F. None of above. chosen
Provenance (4 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02067e8d8819090a006cb266da5fe |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b147cc081909237f3f2967d4cb8 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:37 p.m.