Triple
T13239778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Girona–Costa Brava Airport |
E315249
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
GRO
GRO is the IATA airport code for Girona–Costa Brava Airport, a regional airport in Catalonia, Spain that serves the city of Girona and the nearby Costa Brava tourist area.
|
E1028505
|
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: GRO | Statement: [Girona–Costa Brava Airport, IATAcode, GRO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GRO Context triple: [Girona–Costa Brava Airport, IATAcode, GRO]
-
A.
GRO
GRO is the FAA airport code assigned to Rota International Airport, a public airport serving the island of Rota in the Northern Mariana Islands.
-
B.
GRO
GRO is the commonly used acronym for the Compton Gamma Ray Observatory, a NASA space telescope that studied high-energy gamma-ray sources in the universe.
-
C.
GRO
GRO is the station code used to identify Grove Street station on the Newark Light Rail system in New Jersey.
-
D.
GROM
GROM is Poland’s elite special operations unit renowned for high-risk counterterrorism, hostage rescue, and unconventional warfare missions.
-
E.
GRA
GRA is the ring-shaped orbital motorway encircling Rome, Italy, serving as a major traffic artery for the metropolitan area.
- 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: GRO Triple: [Girona–Costa Brava Airport, IATAcode, GRO]
Generated description
GRO is the IATA airport code for Girona–Costa Brava Airport, a regional airport in Catalonia, Spain that serves the city of Girona and the nearby Costa Brava tourist area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GRO Target entity description: GRO is the IATA airport code for Girona–Costa Brava Airport, a regional airport in Catalonia, Spain that serves the city of Girona and the nearby Costa Brava tourist area.
-
A.
GRO
GRO is the FAA airport code assigned to Rota International Airport, a public airport serving the island of Rota in the Northern Mariana Islands.
-
B.
GRO
GRO is the commonly used acronym for the Compton Gamma Ray Observatory, a NASA space telescope that studied high-energy gamma-ray sources in the universe.
-
C.
GRO
GRO is the station code used to identify Grove Street station on the Newark Light Rail system in New Jersey.
-
D.
GROM
GROM is Poland’s elite special operations unit renowned for high-risk counterterrorism, hostage rescue, and unconventional warfare missions.
-
E.
GRA
GRA is the ring-shaped orbital motorway encircling Rome, Italy, serving as a major traffic artery for the metropolitan area.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5850ac8190849a51da39efe5be |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff323a3c8190b46b24e69e653105 |
completed | May 3, 2026, 7:54 a.m. |
| NEDg | Description generation | batch_69f7013b3428819083c2bb6032aa08d4 |
completed | May 3, 2026, 8:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f702b40f088190bc3c24321309dfb1 |
completed | May 3, 2026, 8:09 a.m. |
Created at: April 9, 2026, 9:23 p.m.