Triple
T34142851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Bras d'Or Channel |
E875763
|
entity |
| Predicate | hasAdjacentHeadland |
P194672
|
FINISHED |
| Object | Cape Dauphin |
—
|
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: Cape Dauphin | Statement: [Great Bras d'Or Channel, hasAdjacentHeadland, Cape Dauphin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacentHeadland Context triple: [Great Bras d'Or Channel, hasAdjacentHeadland, Cape Dauphin]
-
A.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
B.
hasHeadNear
Indicates that one entity’s head is positioned close to another entity or reference point in space.
-
C.
hasAdjacentStationOnAC
Indicates that one station is directly next to another station along the AC line or route.
-
D.
hasAdjacentStationOnM
Indicates that one station is directly next to another station along metro line M, with no other stations in between.
-
E.
hasAdjacentSettlement
Indicates that one settlement is located directly next to or bordering another settlement.
- F. None of above. chosen
Provenance (4 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_69f349aaeef08190a20e72a3fdeb7052 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
| PDg | Predicate description generation | batch_69fd7fd9be2881908a7f00e0e8822de8 |
completed | May 8, 2026, 6:16 a.m. |
Created at: May 1, 2026, 1:54 a.m.