Triple
T18229148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outer Circuit |
E436496
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Sakhir |
—
|
NE NERFINISHED |
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: Sakhir | Statement: [Outer Circuit, locatedIn, Sakhir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sakhir Context triple: [Outer Circuit, locatedIn, Sakhir]
-
A.
Sakhir
chosen
Sakhir is a desert area in Bahrain known for hosting major national institutions and events, including universities and the Bahrain International Circuit.
-
B.
Sakhir Air Base
Sakhir Air Base is a military airfield in Bahrain that serves as a key aviation facility and hosts events such as the Bahrain International Airshow.
-
C.
Al-Doha
Al-Doha is a Palestinian town located in the Bethlehem Governorate of the West Bank.
-
D.
Al Taweelah
Al Taweelah is an industrial and port area in Abu Dhabi, United Arab Emirates, known for major energy and manufacturing facilities including large power, desalination, and aluminum production plants.
-
E.
Al Gharafa
Al Gharafa is a professional football club based in Al Gharafa, Qatar, known for competing in the Qatar Stars League.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b1b2108190a5585bbfaf2d295b |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 10, 2026, 10:33 a.m.