Triple
T5073991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STC Metro |
E114346
|
entity |
| Predicate | line |
P1293
|
FINISHED |
| Object | Line 5 |
E452470
|
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 5 | Statement: [STC Metro, line, Line 5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 5 Context triple: [STC Metro, line, Line 5]
-
A.
Line 5
Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
-
B.
Line 5
Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
-
C.
Line 5
Line 5 is a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
-
D.
Line 5
Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
-
E.
Line 5
chosen
Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
- 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74d0be1c819081b26235fe602a30 |
completed | March 20, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba689ee081909a6bb75c6da07db5 |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:39 p.m.