Triple
T21570980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAH |
E532280
|
entity |
| Predicate | associatedWithUNLocationCodeType |
P1492
|
FINISHED |
| Object | UN/LOCODE (via airport) |
—
|
LITERAL 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: UN/LOCODE (via airport) | Statement: [SAH, associatedWithUNLocationCodeType, UN/LOCODE (via airport)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithUNLocationCodeType Context triple: [SAH, associatedWithUNLocationCodeType, UN/LOCODE (via airport)]
-
A.
associatedWithUnit
Indicates that one entity has a connection, linkage, or affiliation with a particular unit (such as a division, department, or organizational subunit).
-
B.
hasUNLocode
chosen
Indicates that an entity is associated with a specific UN/LOCODE, identifying its location in the United Nations location code system.
-
C.
associatedWithStateCode
Indicates that an entity has a connection or linkage to a particular state identified by its state code.
-
D.
associatedWithLocality
Indicates a relationship where something has a connection or relevance to a specific geographic place or locality.
-
E.
hasUNCode
Indicates that an entity is associated with a specific United Nations–assigned code that identifies it in UN systems or classifications.
- F. None of above.
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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9cc5c448190887a836f577d01ba |
completed | April 27, 2026, 4:45 a.m. |
| PD | Predicate disambiguation | batch_69e6320c8c2c81908bf031447d66a052 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:30 p.m.