Triple
T2477635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Jefferson |
E55124
|
entity |
| Predicate | approximateNumberOfBricks |
P7832
|
FINISHED |
| Object | over 16 million |
—
|
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: over 16 million | Statement: [Fort Jefferson, approximateNumberOfBricks, over 16 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfBricks Context triple: [Fort Jefferson, approximateNumberOfBricks, over 16 million]
-
A.
numberBuilt
Indicates the total count of items or structures that have been constructed or produced.
-
B.
numberOfBoxes
Indicates the quantity or count of boxes associated with a given entity or context.
-
C.
estimatedNumberOfBlocks
chosen
Indicates the approximate count of discrete blocks associated with or involved in the given entity or context.
-
D.
approximateNumberOfMoai
Indicates that one entity specifies an estimated or approximate count of Moai associated with another entity.
-
E.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
- 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_69ab49e279e88190ab10d7248aea9d11 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd1eb3be481908fa7c6b8f1c78209 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b5e3d481909a5cbc4a96edd24f |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.