Triple
T8021062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zheng He |
E186741
|
entity |
| Predicate | sailedTo |
P12804
|
FINISHED |
| Object | Aden |
E22158
|
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: Aden | Statement: [Zheng He, sailedTo, Aden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aden Context triple: [Zheng He, sailedTo, Aden]
-
A.
Aden
chosen
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.
-
B.
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.
-
C.
Al Hudaydah
Al Hudaydah is a key Red Sea port city in western Yemen that serves as one of the country’s main commercial and strategic hubs.
-
D.
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.
-
E.
Arafo
Arafo is a small municipality on the island of Tenerife in Spain’s Canary Islands, known for its rural landscapes and traditional Canarian character.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e8d90488190b57d1e748e272061 |
completed | March 31, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56c82824819082e93eddc40bfad1 |
completed | March 31, 2026, 11:20 p.m. |
Created at: March 30, 2026, 5:20 p.m.