Triple
T4039850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon–Saint-Exupéry Airport |
E83919
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
LFLL
LFLL is the ICAO airport code for Lyon–Saint-Exupéry Airport, a major international airport serving the city of Lyon in France.
|
E408821
|
NE FINISHED |
How this triple was built (4 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: LFLL | Statement: [Lyon–Saint-Exupéry Airport, ICAOcode, LFLL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LFLL Context triple: [Lyon–Saint-Exupéry Airport, ICAOcode, LFLL]
-
A.
LF
LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
-
B.
LLFPA
LLFPA is a U.S. federal law that strengthens workers’ ability to challenge pay discrimination by resetting the statute of limitations with each discriminatory paycheck.
-
C.
LFL
LFL is the former New York Stock Exchange ticker symbol for LAN Airlines, a major Chilean airline that later became part of LATAM Airlines Group.
-
D.
LL
LL is the German vehicle registration code assigned to the district of Landsberg am Lech in Bavaria.
-
E.
LFPO
LFPO is the ICAO airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: LFLL Triple: [Lyon–Saint-Exupéry Airport, ICAOcode, LFLL]
Generated description
LFLL is the ICAO airport code for Lyon–Saint-Exupéry Airport, a major international airport serving the city of Lyon in France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LFLL Target entity description: LFLL is the ICAO airport code for Lyon–Saint-Exupéry Airport, a major international airport serving the city of Lyon in France.
-
A.
LF
LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
-
B.
LLFPA
LLFPA is a U.S. federal law that strengthens workers’ ability to challenge pay discrimination by resetting the statute of limitations with each discriminatory paycheck.
-
C.
LFL
LFL is the former New York Stock Exchange ticker symbol for LAN Airlines, a major Chilean airline that later became part of LATAM Airlines Group.
-
D.
LL
LL is the German vehicle registration code assigned to the district of Landsberg am Lech in Bavaria.
-
E.
LFPO
LFPO is the ICAO airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
- F. None of above. chosen
Provenance (5 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb39400881909d0f5430f04e441c |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b55649b75c819086b272f56ac73be4 |
completed | March 14, 2026, 12:36 p.m. |
| NEDg | Description generation | batch_69b55a1974348190b6c8ca74fb9da47e |
completed | March 14, 2026, 12:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b55a828d7881908e3e9a14bc77103c |
completed | March 14, 2026, 12:54 p.m. |
Created at: March 9, 2026, 3:37 p.m.