Triple
T3672557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Napoleon’s Tomb (Valley of the Geraniums / Sane Valley) |
E77912
|
entity |
| Predicate | distanceFromLongwoodHouse |
P50094
|
FINISHED |
| Object | approximately 1.5 km |
—
|
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: approximately 1.5 km | Statement: [Napoleon’s Tomb (Valley of the Geraniums / Sane Valley), distanceFromLongwoodHouse, approximately 1.5 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLongwoodHouse Context triple: [Napoleon’s Tomb (Valley of the Geraniums / Sane Valley), distanceFromLongwoodHouse, approximately 1.5 km]
-
A.
distanceFromCampusCenter
Indicates the measured or specified distance between a given location and the central point of the campus.
-
B.
distanceFromChestnutHillCampus
Indicates the spatial distance between a given entity and the Chestnut Hill campus.
-
C.
distanceFromFord’sTheatre
Indicates the spatial distance between an entity and Ford’s Theatre.
-
D.
distanceToWashingtonDC
Indicates the physical distance between a given location and Washington, D.C.
-
E.
distanceFromGeorgeTown
Indicates the measured spatial distance between a given location and George Town.
- 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42f82548190b4d5f0fe7250decb |
completed | March 8, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69adb84a20288190a092e4a1b045fe3f |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb8e4ba948190a9b777cf7f788b96 |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:25 p.m.