Triple
T6944202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taif Regional Airport |
E160753
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Taif |
E87275
|
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: Taif | Statement: [Taif Regional Airport, serves, Taif]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taif Context triple: [Taif Regional Airport, serves, Taif]
-
A.
Taif
chosen
Taif is a city in western Saudi Arabia known for its cool climate, rose cultivation, and historical significance as a summer resort and cultural center.
-
B.
Taihoku
Taihoku was the Japanese colonial-era name for Taipei, which served as the administrative and political center of Taiwan under Japanese rule.
-
C.
Te Kao
Te Kao is a small rural community at the northern end of New Zealand’s North Island, known for its strong Māori heritage and proximity to Ninety Mile Beach.
-
D.
Toda
Toda is a subgroup of the Seediq, an Indigenous people of Taiwan known for their distinct language and cultural traditions.
-
E.
Tiba
Tiba is a modern planned city in Egypt’s Luxor Governorate, developed to accommodate population growth and support regional economic and urban expansion.
- 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da88b79c8190a8f297dfc4972979 |
completed | March 27, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c75866a2408190b472fdad73a8799b |
completed | March 28, 2026, 4:26 a.m. |
Created at: March 27, 2026, 2:28 p.m.