Triple
T7373129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCoy Air Force Base |
E170056
|
entity |
| Predicate | namedFeaturePreservedIn |
P17760
|
FINISHED |
| Object | airport code MCO |
—
|
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: airport code MCO | Statement: [McCoy Air Force Base, namedFeaturePreservedIn, airport code MCO]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedFeaturePreservedIn Context triple: [McCoy Air Force Base, namedFeaturePreservedIn, airport code MCO]
-
A.
preservesFeature
chosen
Indicates that one entity maintains or keeps intact a particular feature, property, or characteristic of another entity during some process or interaction.
-
B.
namedFeature
Indicates that an entity has a specific feature or attribute that is explicitly given a name.
-
C.
withinFeature
Indicates that one entity is spatially contained inside or lies entirely within the bounds of another feature.
-
D.
originalFeature
Indicates that one entity is the initial or source feature from which another feature is derived, modified, or referenced.
-
E.
protectsFeature
Indicates that one entity safeguards, preserves, or defends a particular feature or characteristic of another 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1a50898819087097a64e09e19eb |
completed | March 27, 2026, 9:07 p.m. |
| PD | Predicate disambiguation | batch_69c6f02ee3e08190a7a00c981129b22c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:07 p.m.