Triple
T5951613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The House of the Seven Gables |
E132410
|
entity |
| Predicate | roofCount |
P66952
|
FINISHED |
| Object | seven gables |
—
|
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: seven gables | Statement: [The House of the Seven Gables, roofCount, seven gables]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roofCount Context triple: [The House of the Seven Gables, roofCount, seven gables]
-
A.
roofLevel
Indicates the vertical level or story of a building at which the roof is located or begins.
-
B.
roofHeight
Indicates the vertical distance or elevation of a roof relative to a reference level or structure.
-
C.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
D.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
E.
floorCountOfSurroundingBuildings
Indicates the number of floors in the buildings that are located around or near a given reference building or area.
- 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03edf98b881908e9dbc03d3fd6218 |
completed | March 22, 2026, 7:11 p.m. |
Created at: March 22, 2026, 4:02 p.m.