Triple
T35925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baltimore/Washington International Thurgood Marshall Airport |
E711
|
entity |
| Predicate | hasConcourses |
P1656
|
FINISHED |
| Object | Concourses A, B, C, D, E |
—
|
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: Concourses A, B, C, D, E | Statement: [Baltimore/Washington International Thurgood Marshall Airport, hasConcourses, Concourses A, B, C, D, E]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConcourses Context triple: [Baltimore/Washington International Thurgood Marshall Airport, hasConcourses, Concourses A, B, C, D, E]
-
A.
hasConcourse
chosen
Indicates that an entity includes, is connected to, or is served by a concourse area (such as a passageway or central hall).
-
B.
hasCompetition
Indicates that one entity is in a state of rivalry or contest with another entity, typically competing for the same goal, resource, or advantage.
-
C.
convenes
Indicates bringing people or groups together to formally meet, discuss, or deliberate on a particular matter.
-
D.
hasReception
Indicates that an entity hosts, includes, or is associated with a reception event (such as a formal gathering or welcoming function).
-
E.
hasChallenge
Indicates that an entity faces, experiences, or is confronted with a particular difficulty, obstacle, or problem.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24bb753f081909cd8b25cfb8e08af |
completed | Feb. 28, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69a24ab4a6908190b6f355415ffe7948 |
completed | Feb. 28, 2026, 1:53 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.