Triple
T586156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amsterdam Airport Schiphol |
E15161
|
entity |
| Predicate | hasTerminalConfiguration |
P13644
|
FINISHED |
| Object | single-terminal |
—
|
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: single-terminal | Statement: [Amsterdam Airport Schiphol, hasTerminalConfiguration, single-terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerminalConfiguration Context triple: [Amsterdam Airport Schiphol, hasTerminalConfiguration, single-terminal]
-
A.
hasConfiguration
chosen
Indicates that an entity is associated with or defined by a particular configuration or setup.
-
B.
hasSubTerminal
Indicates that an entity includes or is associated with a subordinate or lower-level terminal element within a hierarchical structure.
-
C.
hasVIPTerminal
Indicates that one entity possesses or provides access to a VIP (very important person) terminal associated with another entity.
-
D.
hasTerminatingPlatforms
Indicates that the subject location or facility includes platforms where rail or transit services begin or end their routes, rather than passing through.
-
E.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an entity.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9a46388190a094b9ebf8dec397 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494ca68448190a516b9c3525d8916 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.