Triple
T10574788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 4 (Barcelona Metro) |
E249580
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Línia 4 |
E270679
|
NE 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: Línia 4 | Statement: [Line 4 (Barcelona Metro), alsoKnownAs, Línia 4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Línia 4 Context triple: [Line 4 (Barcelona Metro), alsoKnownAs, Línia 4]
-
A.
Metro Line 4
chosen
Metro Line 4 is a rapid transit route within a city's metro system that connects with other lines, including Metro Line 6, to facilitate passenger transfers across the network.
-
B.
Línea 6
Línea 6 is a modern, fully automated metro line in Santiago, Chile, known for its advanced technology, safety features, and connection between key residential and commercial areas of the city.
-
C.
Línea 6
Línea 6 is a circular line of the Madrid Metro that loops around the city, connecting many major transfer stations and neighborhoods.
-
D.
S4 line
The S4 line is a suburban railway service of the Zürich S-Bahn network that connects the city of Zürich with surrounding regional destinations.
-
E.
S4 line
The S4 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt metropolitan area, including central hubs such as Frankfurt Hauptwache.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52749dda08190b0c9627a931c5848 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b5d89748190bb398943e4a16e9b |
completed | April 10, 2026, 7:11 p.m. |
Created at: April 6, 2026, 12:38 p.m.