Triple
T7823242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reina Sofía Airport |
E181182
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object | TFS |
E170976
|
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: TFS | Statement: [Reina Sofía Airport, IATAcode, TFS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TFS Context triple: [Reina Sofía Airport, IATAcode, TFS]
-
A.
TFS
chosen
TFS is the IATA airport code for Tenerife South Airport, a major international gateway to Spain’s Canary Islands.
-
B.
TFS
TFS is the Texas A&M Forest Service, a state agency that manages and protects Texas’s forests and related natural resources.
-
C.
Perforce
Perforce is a centralized version control system widely used in game development and large-scale software projects for its performance and robust asset management.
-
D.
TeamSystem
TeamSystem is an Italian software company specializing in business management and accounting solutions for small and medium-sized enterprises.
-
E.
TeamCity
TeamCity is a commercial continuous integration and build management server developed by JetBrains, used to automate building, testing, and deploying software projects.
- 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cafa095d7081908b3e492ce58b5d5f |
completed | March 30, 2026, 10:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb14a526cc8190a8b1a3179f75ad6c |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 4:42 p.m.