Triple
T24764697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EGH |
E619547
|
entity |
| Predicate | stationFullName |
P8935
|
FINISHED |
| Object | Egham railway station |
—
|
NE NERFINISHED |
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: Egham railway station | Statement: [EGH, stationFullName, Egham railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stationFullName Context triple: [EGH, stationFullName, Egham railway station]
-
A.
stationName
chosen
Indicates the name assigned to a particular station in the relationship.
-
B.
stationSlogan
Indicates the promotional phrase or tagline that is used to represent or advertise a particular station.
-
C.
stationType
Indicates the specific category or classification of a station based on its function, services, or operational characteristics.
-
D.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
-
E.
stationComplex
Indicates a relationship where one entity is a station complex that encompasses or is associated with another station-related entity.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a4591c81909f918efd84a1f6f6 |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:28 a.m.