Triple
T18122067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pont de Rennes Bridge |
E433763
|
entity |
| Predicate | spansArea |
P66139
|
FINISHED |
| Object | High Falls district |
—
|
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: High Falls district | Statement: [Pont de Rennes Bridge, spansArea, High Falls district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spansArea Context triple: [Pont de Rennes Bridge, spansArea, High Falls district]
-
A.
includesAreaOf
Indicates that one entity encompasses or contains the spatial extent or area covered by another entity.
-
B.
baySpanned
Indicates that a structure or feature extends across and covers the width of a bay.
-
C.
underliesArea
Indicates that one entity forms the foundational basis or underlying support for a particular area or domain of activity, knowledge, or influence.
-
D.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
E.
coveredArea
chosen
Indicates that one entity occupies or extends over a specific spatial region or surface area associated with another entity.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddeb2d7881909326cb9d2f5e2fb5 |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:28 a.m.