Triple
T16159289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bursa Yenişehir Airport |
E392133
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | DHMİ |
E381685
|
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: DHMİ | Statement: [Bursa Yenişehir Airport, operator, DHMİ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DHMİ Context triple: [Bursa Yenişehir Airport, operator, DHMİ]
-
A.
DHMİ
chosen
DHMİ is Turkey’s state-owned General Directorate of State Airports Authority, responsible for operating and managing the country’s major airports and air navigation services.
-
B.
DHM
DHM is the National Rail station code for Durham railway station in County Durham, England.
-
C.
DHM
DHM is the commonly used abbreviation for the German Historical Museum in Berlin, a major institution dedicated to documenting and presenting German history.
-
D.
DHM
DHM is the IATA airport code for Kangra Airport, a regional airport serving Dharamshala and the surrounding Kangra Valley in Himachal Pradesh, India.
-
E.
HdM
HdM is the commonly used abbreviation for Stuttgart Media University, a German university specializing in media, information, and communication studies.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e5de3c481908eb5cdf194a47ff7 |
completed | April 17, 2026, 11:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7b05a588190a44d1c922195a87b |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.