Triple
T16799719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kauai Test Facility |
E408323
|
entity |
| Predicate | hasRunwayOrPad |
P124679
|
FINISHED |
| Object | rocket launch pads |
—
|
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: rocket launch pads | Statement: [Kauai Test Facility, hasRunwayOrPad, rocket launch pads]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayOrPad Context triple: [Kauai Test Facility, hasRunwayOrPad, rocket launch pads]
-
A.
hasRunwayPresence
Indicates that an entity maintains a physical runway or landing strip suitable for aircraft operations.
-
B.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
-
C.
hasRunwaySide
Indicates that a runway is located on or associated with a particular side or boundary of another feature (such as an airport or airfield area).
-
D.
hasRunwayCount
Indicates the number of runways that a given entity (such as an airport) possesses.
-
E.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2acd3548190a5f6ce7d1cf74117 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.