Triple
T8715908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaillard Cut |
E206892
|
entity |
| Predicate | minimumWidthAfterWidening |
P12977
|
FINISHED |
| Object | about 192 meters |
—
|
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: about 192 meters | Statement: [Gaillard Cut, minimumWidthAfterWidening, about 192 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumWidthAfterWidening Context triple: [Gaillard Cut, minimumWidthAfterWidening, about 192 meters]
-
A.
minimumWidth
chosen
Indicates that there is a specified smallest allowable or required width for something in the relationship.
-
B.
maximumChannelWidth
Indicates the greatest allowable or observed width of a channel in the given context.
-
C.
hasApproximateMaximumWidth
Indicates that an entity’s maximum width is known only approximately, rather than as an exact value.
-
D.
encodingWidth
Indicates the width dimension used when encoding a signal, image, or data stream.
-
E.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd807cc819090b58caf285b397a |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.