Triple
T993246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yemeni Revolution of 2011 |
E21437
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Taiz |
E113390
|
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: Taiz | Statement: [Yemeni Revolution of 2011, location, Taiz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taiz Context triple: [Yemeni Revolution of 2011, location, Taiz]
-
A.
Taiz
chosen
Taiz is one of Yemen’s largest and historically most important cities, known as a cultural and intellectual center in the country.
-
B.
Sanaʽa
Sanaʽa is the historic capital and one of the largest cities of Yemen, renowned for its ancient architecture and cultural significance in the Arabian Peninsula.
-
C.
Sanaa
Sanaa is a table-service restaurant at Disney’s Animal Kingdom Lodge known for its African-inspired cuisine with Indian flavors and savanna views of roaming wildlife.
-
D.
Beni Mellal
Beni Mellal is a major city in central Morocco known for its agricultural importance and its location at the foot of the Middle Atlas mountains.
-
E.
Kufa
Kufa is an ancient Iraqi city that became an early Islamic cultural and religious center, historically renowned as a hub of scholarship and calligraphy.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4c3f7b48190a31308bdc09817c6 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac537d788c81908d239f102626bdd6 |
completed | March 7, 2026, 4:34 p.m. |
Created at: March 1, 2026, 7:41 p.m.