Triple
T290624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biggin Hill |
E5982
|
entity |
| Predicate | airfieldEstablished |
P7893
|
FINISHED |
| Object | First World War era |
—
|
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: First World War era | Statement: [Biggin Hill, airfieldEstablished, First World War era]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airfieldEstablished Context triple: [Biggin Hill, airfieldEstablished, First World War era]
-
A.
openedAsMilitaryAirfield
chosen
Indicates that an airfield was originally established and began operation specifically for military aviation use.
-
B.
containsAirfield
Indicates that a location or area includes at least one airfield within its boundaries.
-
C.
largestAirport
Indicates that one airport is the largest (typically by area, traffic, or capacity) among a specified set or within a given region.
-
D.
hasInternationalAirport
Indicates that a place possesses an airport that handles international flights and services cross-border air traffic.
-
E.
hasAirportClassification
Indicates that an airport is assigned a specific classification or category based on defined criteria.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e4f78bc81909a64fd6aaec3b504 |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7d089081909810442c3d0182f6 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.