Triple
T13432377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanabad |
E313643
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Tus |
E120194
|
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: Tus | Statement: [Sanabad, locatedNear, Tus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tus Context triple: [Sanabad, locatedNear, Tus]
-
A.
Tus
Tus is a supporting character in the video game "Prince of Persia: The Sands of Time," serving as one of the Prince’s royal relatives and a military leader.
-
B.
Tus
chosen
Tus is an ancient city in northeastern Iran, renowned as a cultural and literary center and traditionally regarded as the birthplace and home of the Persian epic poet Ferdowsi.
-
C.
TUS
TUS is the three-letter IATA airport code for Tucson International Airport, the primary commercial airport serving Tucson, Arizona.
-
D.
Tu
Tu Youyou is a Chinese pharmaceutical chemist and Nobel laureate renowned for discovering the antimalarial drug artemisinin.
-
E.
Tu
The Tu are a Mongolic-speaking ethnic minority in northwestern China, known for their Tibetan Buddhist traditions and distinctive agrarian culture in Qinghai and Gansu provinces.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed41a5481908800033303224adb |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7398da07081908c3eca6fc4213930 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:40 p.m.