Triple
T1493476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Trafford tram stop |
E29633
|
entity |
| Predicate | hasShelterType |
P3789
|
FINISHED |
| Object | covered waiting areas |
—
|
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: covered waiting areas | Statement: [Old Trafford tram stop, hasShelterType, covered waiting areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShelterType Context triple: [Old Trafford tram stop, hasShelterType, covered waiting areas]
-
A.
hasShelters
chosen
Indicates that one entity provides, contains, or is associated with one or more shelters for another entity or purpose.
-
B.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
C.
canAdopt
Indicates that one entity has the ability or permission to adopt another entity.
-
D.
hasZoo
Indicates that one entity possesses, operates, or is associated with a zoo.
-
E.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c665488190ae665f7a1b0563f5 |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c48902808190a8028d359bcf123e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.