Triple
T11955922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EFKA |
E284552
|
entity |
| Predicate | hasStandardCode |
P102462
|
FINISHED |
| Object | ICAO airport code |
—
|
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: ICAO airport code | Statement: [EFKA, hasStandardCode, ICAO airport code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandardCode Context triple: [EFKA, hasStandardCode, ICAO airport code]
-
A.
isStandard
Indicates that something conforms to an established norm, specification, or commonly accepted rule.
-
B.
hasStandardType
Indicates that something conforms to or is categorized under a defined standard classification or type.
-
C.
hasStructureCode
Indicates that an entity is associated with a specific structural identifier or code that defines its organization or configuration.
-
D.
hasGssCode
Indicates that an entity is associated with a specific GSS (Government Statistical Service) code used for official geographic or statistical identification.
-
E.
hasProgramCode
Indicates that an entity is associated with a specific program identifier or code used to reference or classify it within a system.
- F. None of above. chosen
Provenance (4 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90366fda8819083168c93abad27d4 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:45 p.m.