Triple
T26715878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secane |
E673556
|
entity |
| Predicate | adjacentTownship |
P165353
|
FINISHED |
| Object | Springfield Township, Delaware County, Pennsylvania |
—
|
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: Springfield Township, Delaware County, Pennsylvania | Statement: [Secane, adjacentTownship, Springfield Township, Delaware County, Pennsylvania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentTownship Context triple: [Secane, adjacentTownship, Springfield Township, Delaware County, Pennsylvania]
-
A.
neighboringTownship
chosen
Indicates that two townships share a common boundary and are directly adjacent to each other.
-
B.
adjacentProvince
Indicates that two provinces share a common boundary and are directly next to each other geographically.
-
C.
neighbouringMunicipality
Indicates that one municipality directly borders and is adjacent to another municipality.
-
D.
neighboringRegion
Indicates that two regions share a common boundary or are directly adjacent to each other geographically.
-
E.
adjacentToCounty
Indicates that one county directly borders or touches another county geographically.
- 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_69eecda3a22881908f3061c760b9d542 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 27, 2026, 3:37 a.m.