Triple
T3765895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TAV Airports |
E82675
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | TAV İşletme Hizmetleri |
E285091
|
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: TAV İşletme Hizmetleri | Statement: [TAV Airports, subsidiary, TAV İşletme Hizmetleri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TAV İşletme Hizmetleri Context triple: [TAV Airports, subsidiary, TAV İşletme Hizmetleri]
-
A.
T-Engineering
T-Engineering is an engineering firm known for its role in designing major infrastructure projects, including the Yavuz Sultan Selim Bridge in Turkey.
-
B.
TAV Airports (stakeholder)
TAV Airports is a major Turkish airport operator and services company managing and developing airports primarily in Turkey and other international markets.
-
C.
TAP Group
TAP Group is the holding company that owns and oversees TAP Air Portugal and its related aviation and travel businesses.
-
D.
TAV Airports Holding
chosen
TAV Airports Holding is a Turkish airport operating company that manages and develops a network of airports primarily in Turkey and other countries.
-
E.
Tarsus Group
Tarsus Group is an international business-to-business media and events company known for organizing major trade shows, exhibitions, and conferences worldwide.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbfeb52081909c38103beb5dbdcd |
completed | March 8, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e5221ab08190a3599afbbd5dbc6e |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:35 p.m.