Triple
T4615923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 1D |
E100867
|
entity |
| Predicate | flightRangeFocus |
P57459
|
FINISHED |
| Object | short-haul |
—
|
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 | Statement: [Terminal 1D, flightRangeFocus, short-haul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flightRangeFocus Context triple: [Terminal 1D, flightRangeFocus, short-haul]
-
A.
flightLevelRange
Indicates the range of permissible or actual flight levels associated with an aircraft’s operation or a specific flight segment.
-
B.
landingDistance
Indicates the required or actual distance needed for an aircraft or object to complete a landing from approach to full stop.
-
C.
flightPeriod
Indicates the time span during which a flight occurs or is scheduled to operate.
-
D.
flightDuration
Indicates the length of time that a specific flight takes from departure to arrival.
-
E.
flightRoute
Indicates a path or sequence of locations that a particular flight travels between, typically from its origin to its destination (and possibly via intermediate stops).
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59df3c3c8190be5db000f831d322 |
completed | March 20, 2026, 2:29 p.m. |
| PD | Predicate disambiguation | batch_69bd522e2d5c8190937d0b5574f78f99 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:12 p.m.