Triple
T12132311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arts-Loi – Kunst-Wet |
E288962
|
entity |
| Predicate | metroLine |
P848
|
FINISHED |
| Object | Line 6 |
E930245
|
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: Line 6 | Statement: [Arts-Loi – Kunst-Wet, metroLine, Line 6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 6 Context triple: [Arts-Loi – Kunst-Wet, metroLine, Line 6]
-
A.
Line 6
Line 6 is a major rapid transit route in the Beijing Subway system that runs east–west across the city, helping to relieve congestion on other central lines.
-
B.
Line 6
Line 6 is a major north–south route of the Tehran Metro system, serving numerous key districts across Iran’s capital city.
-
C.
Line 6
Line 6 is a planned rapid transit route within the future Ho Chi Minh City Metro system in Vietnam.
-
D.
Line 6
Line 6 is a route of the Tunis Metro light rail network serving passengers within the Tunis metropolitan area.
-
E.
Line 6
chosen
Line 6 is one of the lines of the Paris Métro, known for its largely elevated route offering views of the city, including the Eiffel Tower.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158b34648190b5eecdf9b07fbb3f |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f68c8ee081908a0331805f62cb0d |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:49 p.m.