Triple
T15544184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merimbula Airport |
E370559
|
entity |
| Predicate | hasICAOcode |
P419
|
FINISHED |
| Object |
YMER
YMER is the ICAO airport code for Merimbula Airport, a regional airport serving the coastal town of Merimbula in New South Wales, Australia.
|
E1162946
|
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: YMER | Statement: [Merimbula Airport, hasICAOcode, YMER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: YMER Context triple: [Merimbula Airport, hasICAOcode, YMER]
-
A.
Ifremer
Ifremer is the French national institute for ocean science, conducting marine research and operating major oceanographic infrastructures and data centers.
-
B.
Gimirri
Gimirri is the Akkadian name for the ancient nomadic people known as the Cimmerians, who inhabited the Eurasian steppe and raided parts of Anatolia and the Near East.
-
C.
Rigmor
Rigmor is a feminine given name of Scandinavian origin, particularly used in Norway and Denmark.
-
D.
Ourém
Ourém is a historic municipality and pilgrimage destination in central Portugal, best known for its proximity to the Sanctuary of Fátima.
-
E.
Yoreme
Yoreme is the self-designation of the Mayo Indigenous people of northern Mexico, known for their rich cultural traditions, language, and ceremonial practices.
- 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: YMER Triple: [Merimbula Airport, hasICAOcode, YMER]
Generated description
YMER is the ICAO airport code for Merimbula Airport, a regional airport serving the coastal town of Merimbula in New South Wales, Australia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: YMER Target entity description: YMER is the ICAO airport code for Merimbula Airport, a regional airport serving the coastal town of Merimbula in New South Wales, Australia.
-
A.
Ifremer
Ifremer is the French national institute for ocean science, conducting marine research and operating major oceanographic infrastructures and data centers.
-
B.
Gimirri
Gimirri is the Akkadian name for the ancient nomadic people known as the Cimmerians, who inhabited the Eurasian steppe and raided parts of Anatolia and the Near East.
-
C.
Rigmor
Rigmor is a feminine given name of Scandinavian origin, particularly used in Norway and Denmark.
-
D.
Ourém
Ourém is a historic municipality and pilgrimage destination in central Portugal, best known for its proximity to the Sanctuary of Fátima.
-
E.
Yoreme
Yoreme is the self-designation of the Mayo Indigenous people of northern Mexico, known for their rich cultural traditions, language, and ceremonial practices.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0443410408190a249889edcd9c599 |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff455a38188190a593c70be09d6103 |
completed | May 9, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69ff45dbc9dc8190b3cac64e4a418aa3 |
completed | May 9, 2026, 2:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff464571808190bfe7ef3a33d246f1 |
completed | May 9, 2026, 2:35 p.m. |
Created at: April 10, 2026, 4:07 a.m.