Triple
T30356210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chilbolton Observatory |
E772148
|
entity |
| Predicate | hasRunwayOrigin |
P172933
|
FINISHED |
| Object | former RAF Chilbolton airfield |
—
|
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: former RAF Chilbolton airfield | Statement: [Chilbolton Observatory, hasRunwayOrigin, former RAF Chilbolton airfield]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayOrigin Context triple: [Chilbolton Observatory, hasRunwayOrigin, former RAF Chilbolton airfield]
-
A.
hasRunwayPresence
Indicates that an entity maintains a physical runway or landing strip suitable for aircraft operations.
-
B.
hasRunwayUse
Indicates that a particular runway is authorized or designated for use by a specific aircraft, operation, or purpose.
-
C.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
-
D.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
-
E.
hasRunwayAccessTo
Indicates that one location or facility is directly connected to another via a usable runway, allowing aircraft to move between them without leaving runway infrastructure.
- F. None of above. chosen
Provenance (4 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6b2d9aad88190a445f8f591cb19fc |
completed | May 3, 2026, 2:28 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: April 29, 2026, 7:57 p.m.