Triple
T3985823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hendon |
E86868
|
entity |
| Predicate | airfieldOpened |
P53197
|
FINISHED |
| Object | early 20th century |
—
|
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: early 20th century | Statement: [Hendon, airfieldOpened, early 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airfieldOpened Context triple: [Hendon, airfieldOpened, early 20th century]
-
A.
airportOpened
Indicates that an airport began operations or was officially opened at a specific time.
-
B.
openedAsMilitaryAirfield
Indicates that an airfield was originally established and began operation specifically for military aviation use.
-
C.
openedAsMunicipalAirport
Indicates that an airport was initially established and began operation as a municipal (city- or town-operated) airport.
-
D.
openedAsCivilAirport
Indicates that a facility or location began operation specifically as a civil (non-military) airport.
-
E.
containsAirfield
Indicates that a location or area includes at least one airfield within its boundaries.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa3ef7ac8190abe02f440ff83c43 |
completed | March 9, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69aef8f492ac819089dbb9436dbcdd2b |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa3cf4048190837f9ec5fa8e95e3 |
completed | March 9, 2026, 4:50 p.m. |
Created at: March 9, 2026, 3:33 p.m.