Triple
T6809020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arsenal Underground station |
E156582
|
entity |
| Predicate | servesPrimaryUse |
P56223
|
FINISHED |
| Object | football matchday traffic |
—
|
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: football matchday traffic | Statement: [Arsenal Underground station, servesPrimaryUse, football matchday traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesPrimaryUse Context triple: [Arsenal Underground station, servesPrimaryUse, football matchday traffic]
-
A.
servesUse
Indicates that one entity is used by or functions to serve the purpose or needs of another entity.
-
B.
primarilyFor
chosen
Indicates that something is mainly intended, designed, or used for a particular purpose, function, or beneficiary, even if it may have secondary uses.
-
C.
usedPrimarilyIn
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
-
D.
laterPrimarilyUsedFor
Indicates that something was initially used for one purpose but, at a later time, came to be used mainly for another specified purpose.
-
E.
primaryServes
Indicates that one entity’s main or principal function is to serve, support, or provide service to another 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30c741881909e220b05aa564bc2 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:16 p.m.