Triple
T19201142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbey Road zebra crossing, London |
E470108
|
entity |
| Predicate | hasNearbySignage |
P5950
|
FINISHED |
| Object | Abbey Road street signs |
—
|
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: Abbey Road street signs | Statement: [Abbey Road zebra crossing, London, hasNearbySignage, Abbey Road street signs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbySignage Context triple: [Abbey Road zebra crossing, London, hasNearbySignage, Abbey Road street signs]
-
A.
hasSignageIn
Indicates that appropriate signs or signage for an entity are present or installed within a specified location or area.
-
B.
hasTouristSignage
Indicates that there is official signage present to guide or inform tourists about a place, route, or attraction.
-
C.
hasSignage
chosen
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
D.
hasSignageType
Indicates the specific category or kind of signage associated with an object, location, or entity.
-
E.
hasTrailheadSignage
Indicates that a trailhead is equipped with signage providing information or guidance to users.
- 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f997879c8190ae7618d1ba0cede9 |
completed | April 20, 2026, 10:01 a.m. |
| PD | Predicate disambiguation | batch_69e4b9bc158081908307dab01d9478c6 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:07 p.m.