Triple
T36650096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golders Green Underground Station |
E904823
|
entity |
| Predicate | fareZoneFrom2016 |
P129036
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Golders Green Underground Station, fareZoneFrom2016, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareZoneFrom2016 Context triple: [Golders Green Underground Station, fareZoneFrom2016, 3]
-
A.
fareZoneRange
Indicates the range of fare zones within which a ticket, pass, or fare rule is valid or applicable.
-
B.
fareZoneSince
chosen
Indicates the date or time from which a particular fare zone assignment has been in effect for an entity.
-
C.
fareZoneDescription
Indicates the textual description of the fare zone associated with a service, location, or segment.
-
D.
fareZoneCode
Indicates the designated fare zone identifier associated with a location, route, or segment for pricing or ticketing purposes.
-
E.
fareZoneStart
Indicates the fare zone in which a journey, ticket, or pricing calculation begins.
- 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_69f76e6d3a3c81909db73eda9e0516bd |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.