Triple
T36655257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 4 (Ninoy Aquino International Airport) |
E904969
|
entity |
| Predicate | hasSingleLevelStructure |
P196476
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Terminal 4 (Ninoy Aquino International Airport), hasSingleLevelStructure, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSingleLevelStructure Context triple: [Terminal 4 (Ninoy Aquino International Airport), hasSingleLevelStructure, yes]
-
A.
hasStructureLevel
Indicates a relationship where one entity possesses, is assigned, or is characterized by a particular structural level within a hierarchy or layered organization.
-
B.
hasNumberOfLevels
Indicates that an entity possesses a specified count of distinct levels or tiers.
-
C.
hasMultipleLevels
Indicates that something is organized into more than one hierarchical or structural level.
-
D.
hasNoFurtherSubdivisionLevel
Indicates that the referenced entity is at the lowest level of subdivision and cannot be further subdivided into smaller units within the given hierarchy.
-
E.
hasTierStructure
Indicates that something is organized into distinct hierarchical levels or layers within a structured 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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
| PDg | Predicate description generation | batch_69fe38bc3e9c8190838430b22b82503f |
completed | May 8, 2026, 7:25 p.m. |
Created at: May 3, 2026, 4:11 p.m.