Triple
T16551089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Dentistry, University of Jordan |
E402072
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Amman |
E15311
|
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: Amman | Statement: [Faculty of Dentistry, University of Jordan, city, Amman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amman Context triple: [Faculty of Dentistry, University of Jordan, city, Amman]
-
A.
Amman
chosen
Amman is the capital and largest city of Jordan, serving as a major political, economic, and cultural center in the Arab world.
-
B.
Amman
Amman is a revered Hindu mother goddess figure, widely worshipped in South India as a protective and benevolent divine mother.
-
C.
Irbid
Irbid is a large city in northern Jordan known as an important economic, educational, and cultural center.
-
D.
Ma’an
Ma’an is a major city in southern Jordan that serves as an important regional hub and gateway to nearby desert and archaeological sites.
-
E.
Al-Karak
Al-Karak is a historic Jordanian city best known for its imposing Crusader-era hilltop castle overlooking the surrounding region.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fc56f9081908bb8f6433a1a688d |
completed | April 18, 2026, 9:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ecfd99c8190a4375a0f62aa50d1 |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:15 a.m.