Triple
T28334965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie R. Tower |
E717644
|
entity |
| Predicate | aircraftTestFlown |
P17100
|
FINISHED |
| Object | Boeing Model 299 prototype |
—
|
NE NERFINISHED |
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: Boeing Model 299 prototype | Statement: [Leslie R. Tower, aircraftTestFlown, Boeing Model 299 prototype]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftTestFlown Context triple: [Leslie R. Tower, aircraftTestFlown, Boeing Model 299 prototype]
-
A.
aircraftFlown
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
-
B.
officiallyFlownOn
Indicates that something has been formally carried or transported aboard a specific flight or aircraft under official or authorized status.
-
C.
notableAircraftTested
chosen
Indicates that the subject conducted tests or evaluations on the specified aircraft, which is considered notable or significant.
-
D.
hasFlownIn
Indicates that an entity has previously traveled by flying in or on another entity (such as an aircraft or similar vehicle).
-
E.
flightTesting
Indicates the process of evaluating and validating an aircraft or aerospace system’s performance, safety, and functionality through controlled test flights.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 28, 2026, 12:35 a.m.