Triple
T31704889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lynx HMA8 |
E809151
|
entity |
| Predicate | aircrewCapacity |
P177174
|
FINISHED |
| Object | up to 3 |
—
|
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: up to 3 | Statement: [Lynx HMA8, aircrewCapacity, up to 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircrewCapacity Context triple: [Lynx HMA8, aircrewCapacity, up to 3]
-
A.
aircraftCapacity
Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
-
B.
airWingCapacity
Indicates the maximum number or volume of aircraft or air operations that an air wing can support or handle.
-
C.
aircraftPanCapacity
Indicates the maximum number of passengers an aircraft is designed or allowed to carry.
-
D.
aircraftTypicalSeatingCapacity
Indicates the usual number of passenger seats an aircraft is designed or configured to accommodate under normal operating conditions.
-
E.
paratroopCapacity
Indicates the maximum number of paratroopers or amount of airborne troops that something (typically a vehicle or vessel) is capable of carrying or deploying.
- 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f854486c81909396d944a55e03ab |
completed | May 3, 2026, 7:25 a.m. |
Created at: April 30, 2026, 11:13 p.m.