Triple
T15559273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sde Dov |
E370952
|
entity |
| Predicate | formerRunwayUse |
P2417
|
FINISHED |
| Object | short-haul domestic routes |
—
|
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: short-haul domestic routes | Statement: [Sde Dov, formerRunwayUse, short-haul domestic routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerRunwayUse Context triple: [Sde Dov, formerRunwayUse, short-haul domestic routes]
-
A.
previousBuildingUse
Indicates that a building previously served a specified use or function before its current one.
-
B.
usesRunwayOf
Indicates that one entity makes use of the runway that belongs to or is associated with another entity.
-
C.
hasRunwayUse
Indicates that a particular runway is authorized or designated for use by a specific aircraft, operation, or purpose.
-
D.
historicallyUsedFor
chosen
Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
-
E.
formerLandUse
Indicates the type of land use that characterized a location prior to its current or present use.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dda3ab88190ab383333ce69fe8f |
completed | April 16, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:09 a.m.