Triple
T3084081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solent |
E64327
|
entity |
| Predicate | approximateWidthRange |
P13004
|
FINISHED |
| Object | 2–5 miles |
—
|
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: 2–5 miles | Statement: [Solent, approximateWidthRange, 2–5 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateWidthRange Context triple: [Solent, approximateWidthRange, 2–5 miles]
-
A.
hasApproximateMaximumWidth
chosen
Indicates that an entity’s maximum width is known only approximately, rather than as an exact value.
-
B.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
-
C.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
D.
hasWidth
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
E.
hasDimensionsApprox
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
- 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_69ad857bb4c88190a4cf27893fcabed8 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1e98a1c8190b1dd4a0a47f7d6c6 |
completed | March 8, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69ad9debb6308190be28378ae1fc98af |
completed | March 8, 2026, 4:03 p.m. |
Created at: March 8, 2026, 3:03 p.m.