Triple
T492972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Art Museum Steps |
E10227
|
entity |
| Predicate | hasNumberOfFlights |
P4899
|
FINISHED |
| Object | multiple flights of steps |
—
|
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: multiple flights of steps | Statement: [Art Museum Steps, hasNumberOfFlights, multiple flights of steps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfFlights Context triple: [Art Museum Steps, hasNumberOfFlights, multiple flights of steps]
-
A.
numberOfFlights
chosen
Indicates the total count of flights associated with a given entity or within a specified context.
-
B.
hasDomesticFlights
Indicates that an airline or airport operates flights within the same country, connecting domestic destinations.
-
C.
hasInternationalFlights
Indicates that an airport or airline operates flights connecting to destinations in other countries.
-
D.
hasLongHaulFlights
Indicates that an entity (such as an airline, route, or airport) operates or is associated with long-distance flights typically covering intercontinental or extended-duration journeys.
-
E.
numberOfPlanes
Indicates the quantity of planes associated with or involved in a given entity or situation.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f0faab4881909f65f172198b5bd2 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf7ce008190836fb6ab5ea39375 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.