Triple
T5726698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon Metro Line B |
E126282
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | TCL |
E487436
|
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: TCL | Statement: [Lyon Metro Line B, operator, TCL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TCL Context triple: [Lyon Metro Line B, operator, TCL]
-
A.
TCL
chosen
TCL is the public transport network operator serving Lyon and its metropolitan area in France, managing buses, trams, and metro services.
-
B.
TCL Corporation
TCL Corporation is a major Chinese electronics company best known globally for manufacturing televisions and other consumer electronics.
-
C.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
-
D.
Midea
Midea is an important archaeological site in Greece that was a fortified citadel of the Mycenaean civilization.
-
E.
ZTE
ZTE is a major Chinese telecommunications and technology company known for manufacturing network equipment and smartphones and competing globally with firms like Nokia and Huawei.
- 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_69c0082f723881908ce8bb13a0c0f8b7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0250a7f6c8190a264935086608186 |
completed | March 22, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a86eea0819090bf6f9952d8dcc9 |
completed | March 22, 2026, 9:09 p.m. |
Created at: March 22, 2026, 3:47 p.m.