Triple
T10100212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington Market station |
E216179
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object | LEX |
E824291
|
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: LEX | Statement: [Lexington Market station, hasStationCode, LEX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LEX Context triple: [Lexington Market station, hasStationCode, LEX]
-
A.
LEX
LEX is the abbreviation for the Léman Express, a cross-border commuter rail network serving the Greater Geneva region in Switzerland and France.
-
B.
LEX
chosen
LEX is the three-letter IATA airport code for Blue Grass Airport serving Lexington, Kentucky.
-
C.
Lex
Lex is a common shortened form of the given name Alexander, often used as a modern, informal nickname.
-
D.
LEM
LEM is the original abbreviation for the Apollo Lunar Module, the spacecraft used by NASA astronauts to land on and ascend from the Moon during the Apollo missions.
-
E.
LER
LER is the vehicle registration code assigned to the German island municipality of Borkum.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd09878f88190bcfa2c81fb10e821 |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b6cb50b08190a0ff42c60d338c79 |
completed | April 5, 2026, 7:23 p.m. |
Created at: March 30, 2026, 9:02 p.m.