Triple
T25552758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roy S. Geiger |
E640485
|
entity |
| Predicate | pilotWingsAwardedYear |
P158865
|
FINISHED |
| Object | 1917 |
—
|
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: 1917 | Statement: [Roy S. Geiger, pilotWingsAwardedYear, 1917]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pilotWingsAwardedYear Context triple: [Roy S. Geiger, pilotWingsAwardedYear, 1917]
-
A.
issuedFirstPilotLicensesIn
Indicates that an entity granted or distributed its first pilot licenses within a specified time period or at a particular point in time.
-
B.
lastFlightYear
Indicates the calendar year in which an entity’s most recent flight took place.
-
C.
intendedFirstFlightYear
Indicates the year in which an aircraft or aerospace vehicle is planned or expected to make its first flight.
-
D.
yearOfFlight
Indicates the specific calendar year in which a particular flight took place or is scheduled to occur.
-
E.
maidenFlightYear
Indicates the calendar year in which an aircraft or similar vehicle made its first-ever flight.
- 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_69e75dc101a881909fd33b02174e9768 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8c7057881908cca5de0f09a938b |
completed | May 2, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 3:37 p.m.