Triple
T150438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garter Day |
E3417
|
entity |
| Predicate | processionRoute |
P3034
|
FINISHED |
| Object | From Windsor Castle to St George's Chapel |
—
|
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: From Windsor Castle to St George's Chapel | Statement: [Garter Day, processionRoute, From Windsor Castle to St George's Chapel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: processionRoute Context triple: [Garter Day, processionRoute, From Windsor Castle to St George's Chapel]
-
A.
followsRouteOf
Indicates that one entity travels along the same path or route that another entity takes or has taken.
-
B.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
-
C.
transportCorridor
chosen
Indicates a route or pathway used to move people, goods, or resources between locations.
-
D.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
E.
hasApproachRoad
Indicates that one entity is connected to or accessed by another entity via an approach road leading to it.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.