Triple
T9716168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungerford railway station |
E235146
|
entity |
| Predicate | hasTaxiRankNearby |
P24209
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hungerford railway station, hasTaxiRankNearby, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTaxiRankNearby Context triple: [Hungerford railway station, hasTaxiRankNearby, yes]
-
A.
hasTaxiStand
chosen
Indicates that a location or facility includes or is served by a designated taxi stand area where taxis can wait for passengers.
-
B.
hasParkingNearby
Indicates that a location has one or more parking facilities or spaces available within a close surrounding area.
-
C.
hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
-
D.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
E.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
- 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_69ca84cd8fa0819090a5e243ceb37003 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e0bb82081908e21a646f4de1a61 |
completed | April 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69cd03bfeca08190924fca43aaa9c10f |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:20 p.m.