Triple
T7910847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Gardens |
E183693
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Torresdale |
E179995
|
NE 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: Torresdale | Statement: [Academy Gardens, adjacentTo, Torresdale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torresdale Context triple: [Academy Gardens, adjacentTo, Torresdale]
-
A.
Torresdale
chosen
Torresdale is a residential neighborhood in the far northeastern section of Philadelphia, Pennsylvania, known for its proximity to the Delaware River and suburban character.
-
B.
Banwell
Banwell is a village and civil parish in North Somerset, England, known for its historic caves and medieval architecture.
-
C.
Kearsley
Kearsley is a town in Greater Manchester, England, historically part of Lancashire and known for its industrial heritage.
-
D.
Kilndown
Kilndown is a small rural village in Kent, England, known for its historic church and woodland surroundings.
-
E.
Burnage
Burnage is a suburban area of Manchester, England, known primarily as a residential district with good transport links into the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a725b8c8190a530adb3107a95dd |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bdaf91c8190b31c5e539bdf049f |
completed | March 31, 2026, 5:30 a.m. |
Created at: March 30, 2026, 5:04 p.m.