Triple
T4126254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baghdad International Airport |
E92730
|
entity |
| Predicate | hasCivilArea |
P53979
|
FINISHED |
| Object | commercial passenger terminal area |
—
|
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: commercial passenger terminal area | Statement: [Baghdad International Airport, hasCivilArea, commercial passenger terminal area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCivilArea Context triple: [Baghdad International Airport, hasCivilArea, commercial passenger terminal area]
-
A.
hasCivilDivision
Indicates that one administrative or political entity is subdivided into, or is associated with, a specific civil division (such as a county, district, or municipality).
-
B.
hasCivilSection
Indicates that one legal document, case, or record includes or is associated with a specific civil law section or provision.
-
C.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
-
E.
hasCommunityArea
Indicates that an entity is associated with, located in, or belongs to a particular community area.
- 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_69aed9685f70819086932777aec8d959 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af039fb19c8190b20e62a3b3ad25c1 |
completed | March 9, 2026, 5:30 p.m. |
Created at: March 9, 2026, 3:41 p.m.