Triple
T36479242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stapleton Airfield |
E898762
|
entity |
| Predicate | hadTerminalType |
P96660
|
FINISHED |
| Object | passenger 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: passenger terminal | Statement: [Stapleton Airfield, hadTerminalType, passenger terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadTerminalType Context triple: [Stapleton Airfield, hadTerminalType, passenger terminal]
-
A.
has terminal type
chosen
Indicates that an entity is associated with a specific terminal type or category it belongs to.
-
B.
hasIntegratedTerminal
Indicates that one entity includes or supports a built-in terminal interface as part of its functionality.
-
C.
hasPlannedTerminalType
Indicates that an entity is associated with a specific type of terminal that is intended or scheduled to be used in the future.
-
D.
hasTerminalBrand
Indicates that an entity is associated with, or operates under, a specific terminal brand.
-
E.
usedTerminal
Indicates that an entity made use of or interacted with a particular terminal or endpoint device.
- 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_69f76e5a0e088190a2b6706aeb41723c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.