Triple
T13405364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DAI Sana'a Office |
E319940
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Sana'a |
E15731
|
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: Sana'a | Statement: [DAI Sana'a Office, operatesIn, Sana'a]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sana'a Context triple: [DAI Sana'a Office, operatesIn, Sana'a]
-
A.
Sanaʽa
chosen
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.
-
B.
Aden
Aden is a strategic port city in Yemen located on the Gulf of Aden, historically significant as a major maritime hub and former British colonial stronghold.
-
C.
Salalah
Salalah is a coastal city in southern Oman known for its monsoon-cooled climate, lush green landscapes, and role as a regional tourism and commercial hub.
-
D.
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.
-
E.
Sakaka
Sakaka is a city in northwestern Saudi Arabia that serves as the capital of Al-Jawf Province and is known for its ancient archaeological sites and historic forts.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4ae47081909b68a9aaa62fd4c7 |
completed | April 12, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f739857dd4819087e64b956a814939 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:34 p.m.