Triple
T26451103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 4 (Melbourne Airport) |
E665348
|
entity |
| Predicate | hasArrivalLevel |
P170627
|
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 (Melbourne Airport), hasArrivalLevel, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArrivalLevel Context triple: [Terminal 4 (Melbourne Airport), hasArrivalLevel, yes]
-
A.
hasArrivalArea
Indicates that an entity is associated with a specific area designated for arrivals, such as where incoming people or items first enter or are received.
-
B.
hasLevel
Indicates that an entity possesses or is associated with a particular degree, rank, or stage within an ordered scale or hierarchy.
-
C.
hasReach
Indicates that one entity is able to extend its influence, access, or physical span to another entity or area.
-
D.
hasReachUnit
Indicates that one entity uses a specified unit of measurement to express its reach or extent.
-
E.
hasLocalLevel
Indicates that one entity possesses, is associated with, or is defined at a specific local administrative or organizational level relative to another entity.
- 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_69ee883d5040819097dd154643005230 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f693ffa7908190aa4c451b16df9be6 |
completed | May 3, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 27, 2026, 12:05 a.m.