Triple
T13780874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DR |
E331126
|
entity |
| Predicate | hasOnlineService |
P57
|
FINISHED |
| Object | DR LYD |
E216926
|
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: DR LYD | Statement: [DR, hasOnlineService, DR LYD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DR LYD Context triple: [DR, hasOnlineService, DR LYD]
-
A.
LYD
LYD is the station code for Lyon-Part-Dieu, a major high-speed rail hub and one of the main railway stations in Lyon, France.
-
B.
LYD
chosen
LYD is the ISO 4217 currency code for the Libyan dinar, the official currency of Libya.
-
C.
Lys
Lys is a wealthy and decadent island city-state in the world of *A Song of Ice and Fire* known for its pleasure houses, skilled courtesans, and distinctive Valyrian-descended population.
-
D.
Lys
Lys is a utopian, technologically advanced city in Arthur C. Clarke’s early science fiction universe, known for its preserved vitality and contrast to Earth’s stagnation.
-
E.
Lys
The Lys is a river in northern France and western Belgium that flows through cities like Ghent and is known for its historical role in trade and the textile industry.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02460a688190a27874f8d35819c7 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b079013881908e9f5412e5dfb0b2 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:11 p.m.